Search results for: medical assessments

Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

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Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: gripper, haptic, stiffness, robotic

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Authors: Adeniyi Onasanya, Maher Elshakankiri

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In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

Procedia PDF Downloads 177

Authors: Yu-Chih Wang, Chia-Yu Lai, Hsiao-Tien Liu, Yi-Ju Chen, Shao-Bin Cheng

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Liver transplant has been one of the curative treatment options for hepatocellular carcinomaunder certain oncological conditions. Two of the most validated criteria are from Milan in1996 and USCF in 2001, suggesting number and size limits of tumor without vascularinvasion or distant metastasis. We performed a retrospective cohort study of hepatocellular carcinoma patients undergoing livertransplant between August 2003 and December 2020 in our institute. Clinical andpathological characteristic, survival outcome, and recurrent pattern were analysed.UCSF criteria was applied for living donor transplantation, and Milan criteria was applied for deceased donor transplantation. Of 180 total patients, 52 cases(28.8%) with diagnosis of hepatocellular carcinoma, including26 living donor(LD) and 26 deceased donor(DD) liver transplant. Complete pathologicalremission was significantly more in the DD group(p=0.009). Pathological reports showed that30.8% of DD group exceeded Milan criteria, and 19.2% of LD group exceeded UCSFcriteria.After a median follow-up of 52.2 months, the 1-year, 3-year and 5-year overall survival was 87.6%, 74.1%, and 71.8%, respectively.Meanwhile, progression-free survival was 93.1%, 85.7%, and 81.6% for 1, 3, and 5-year, respectively, similar to that in Mazzaferro et al, 1996. We concluded that Liver transplant could be applied cautiously in expanded criteria for patent withhepatocellular carcinoma.

Keywords: liver transplant, milan criteria, UCSF criteria, living donor transplantation, deceased donor transplantation

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Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

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Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of machine learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. With the application of learning methods in such diverse domains, artificial intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been on developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and three defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt machine learning techniques in security-critical areas such as the nuclear industry without rigorous testing since they may be vulnerable to adversarial attacks. While common defence methods can effectively defend against different attacks, none of the three considered can provide protection against all five adversarial attacks analysed.

Keywords: adversarial machine learning, attacks, defences, nuclear industry, crack detection

Procedia PDF Downloads 158

Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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We experience the autopsy cases that the deceased was alive in emergency room on arrival. Bleeding is the leading cause of preventable death after injury. This retrospective study aimed to characterize opportunities for performance improvement identified in patients who died from traffic trauma and were considered by the quality improvement of education system. The Japan Advanced Trauma Evaluation and Care (JATEC) education program was introduced in 2002. We focused the abdominal traffic trauma injury. An autopsy-based cross-sectional study conducted. A purposive sampling technique was applied to select the study sample of 41 post-mortems of road traffic accident between April 1999 and March 2014 subjected to medico-legal autopsy at the department of Forensic Medicine, Shiga University of Medical Science. 16 patients (39.0%) were abdominal trauma injury. The mean period of survival after meet with accident was 13.5 hours, compared abdominal trauma death was 27.4 hours longer. In road traffic accidents, the most injured abdominal organs were liver followed by mesentery. We thought delayed treatment was associated with immediate diagnostic imaging, and so expected to expand trauma management examination.

Keywords: abdominal traffic trauma, preventable death, autopsy, emergency medicine

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Authors: Khaliun Nyambayar, Nomindari Azzaya, Batkhuyag Purevjav

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Pharmacovigilance was officially introduced in Mongolia in 2003, in accordance with the Health Minister Order 183 for the registry of adverse drug reactions (ADR), approved in 2006 and was reviewed in 2010. This study was designed to evaluate the incidence and common types of adverse drug reactions among hospitalized children, the frequency of adverse drug reaction reported by health care providers, and the follow-up processes resulting from adverse drug reactions. A retrospective study of paediatric patients who experienced an adverse drug reaction from 2015 to 2019, extracted from the “yellow” card at the State Research Center for Maternal and Child Health, (city). A total of 417 adverse drug reactions were reported with an overall incidence was 80 (21.5%). Adverse reactions resulting from the use of antibiotics (particularly gentamycin, cephalosporins, and vancomycin) were usually mild. ADR’s were reported by physicians and nurses (93.8%), pharmacists (6.25%). Although documentation of physician notification occurred for 93% of adverse drug reactions, only 29% of cases were documented in the patient's medical chart, 13% included follow-up education for individuals involved, and 10% were updated in the allergy profile of the hospital computer system. Measures to improve the detection and reporting of adverse drug reactions by all health care professionals should be improved, to enhance our understanding of the nature and impact of these reactions in children.

Keywords: adverse drug reaction, pediatric, yellow card, Mongolia

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Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

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Authors: M. D. H. Beg, John O. Akindoyo, Suriati Ghazali, Nitthiyah Jeyaratnam

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Over the period of time, several approaches have been undertaken to mitigate the challenges associated with bone regeneration. This includes but not limited to xenografts, allografts, autografts as well as artificial substitutions like bioceramics, synthetic cements and metals. The former three techniques often come along with peculiar limitation and problems such as morbidity, availability, disease transmission, collateral site damage or absolute rejection by the body as the case may be. Synthetic routes remain the only feasible alternative option for treatment of bone defects. Hydroxyapatite (HA) is very compatible and suitable for this application. However, most of the common methods for HA synthesis are either expensive, complicated or environmentally unfriendly. Interestingly, extraction of HA from bio-wastes have been perceived not only to be cost effective, but also environment friendly. In this research, HA was synthesized from bio-waste: namely bovine bones through three different methods which are hydrothermal chemical processes, ultrasound assisted synthesis and ordinary calcination techniques. Structure and property analysis of the HA was carried out through different characterization techniques such as TGA, FTIR, and XRD. All the methods applied were able to produce HA with similar compositional properties to biomaterials found in human calcified tissues. Calcination process was however observed to be more efficient as it eliminated all the organic components from the produced HA. The HA synthesized is unique for its minimal cost and environmental friendliness. It is also perceived to be suitable for tissue and bone engineering applications.

Keywords: hydroxyapatite, bone, calcination, biowaste

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Authors: Aremu Abdulmujeeb Babatunde

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Background: Low back pain was not only considered to be the most common reason for functional disability worldwide, but also estimated to have affected 90% of the universal population. This study aimed at determining the prevalence, consequences and socio-demographic factors associated with low back pain. Methods; A cross-sectional survey was employed and a total number of 150 self-structured questionnaire was distributed among healthcare workers and this was used to determine the prevalence of low back pain and work related absenteeism. Data was entered using Epi info soft-ware and analyzed using SPSS. Results; An overall response rate of 84% (n = 140) was achieved. The study established that majority (37%) of the respondents were in the age bracket of 20-39 years, 57% female (n=59) and 64% of them were married. the pint prevalence was 84%, 31% of the respondents took leave from work as a result of low back pain. There was high prevalence of sick leave among nursing staff 45.2%, Chi-square test shows that there was a statistically significant association between the respondents occupations and daily time spent during their work (P value 0.011 and 0.042) respectively. Socio-demographic factors like age, marital status and gender were not statistically significant at P<0.05. Conclusions; The medical and socio-professional consequences of low back pain among healthcare workers was as a result of their occupation designations and the daily time spent in carry out this occupations.

Keywords: low back pain, healthcare workers, prevalence, sick leave

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Authors: Xiang Jianhong, Wang Cong, Wang Linyu

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With the rise of medical IoT technologies, Wireless body area networks (WBANs) can collect fetal electrocardiogram (FECG) signals to support telemedicine analysis. The compressed sensing (CS)-based WBANs system can avoid the sampling of a large amount of redundant information and reduce the complexity and computing time of data processing, but the existing algorithms have poor signal compression and reconstruction performance. In this paper, a Joint block multi-orthogonal least squares (JBMOLS) algorithm is proposed. We apply the FECG signal to the Joint block sparse model (JBSM), and a comparative study of sparse transformation and measurement matrices is carried out. A FECG signal compression transmission mode based on Rbio5.5 wavelet, Bernoulli measurement matrix, and JBMOLS algorithm is proposed to improve the compression and reconstruction performance of FECG signal by CS-based WBANs. Experimental results show that the compression ratio (CR) required for accurate reconstruction of this transmission mode is increased by nearly 10%, and the runtime is saved by about 30%.

Keywords: telemedicine, fetal ECG, compressed sensing, joint sparse reconstruction, block sparse signal

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Authors: N. Rassoul-ibrahim, E. Siahmed, L. Tadrist

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Water management plays a crucial role in the performance and durability of PEM fuel cells. Whereas the membrane must be hydrated enough, liquid droplets formed by water in excess can block the flow in the gas distribution channels and hinder the fuel cell performance. The main purpose of this work is to increase the understanding of liquid transport and mixing through mini- or micro-channels for various engineering or medical process applications including cool-ing of equipment according to the operations considered. For that purpose and as a first step, a technique was devel-oped to automatically detect and characterize two-phase flow patterns that may appear in such. The investigation, mainly experimental, was conducted on transparent channel with a 1mm x 1mm square cross section and a 0.3mm x 0.3 mm water injection normal to the gas channel. Three main flow patterns were identified liquid slug, bubble flow and annular flow. A flow map has been built accord-ing to the flow rate of both phases. As a sample the follow-ing figures show representative images of the flow struc-tures observed. An analysis and discussion of the flow pattern, in mini-channel, will be provided and compared to the case old micro-channel. . Keywords: Two phase flow, Clean Energy, Minichannels, Fuel Cells. Flow patterns, Maps.

Keywords: two phase flox, T-juncion, Micro and minichannels, clean energy, flow patterns, maps

Procedia PDF Downloads 76

Authors: Eduardo Lanzagorta Garcia, Chaitra Venkatesh, Romina Pezzoli, Laura Gabriela Rodriguez Barroso, Declan Devine, Margaret E. Brennan Fournet

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New antimicrobial interventions are urgently required to combat rising global health and medical infection challenges. Here, an innovative antimicrobial technology, providing price competitive alternatives to antibiotics and readily integratable with currently technological systems is presented. Two cutting edge antimicrobial materials, antimicrobial peptides (AMPs) and uncompromised sustained Ag+ action from triangular silver nanoplates (TSNPs) reservoirs, are merged for versatile effective antimicrobial action where current approaches fail. Antimicrobial peptides (AMPs) exist widely in nature and have recently been demonstrated for broad spectrum of activity against bacteria, viruses, and fungi. TSNP’s are highly discrete, homogenous and readily functionisable Ag+ nanoreseviors that have a proven amenability for operation within in a wide range of bio-based settings. In a design for advanced antimicrobial sustainable plastics, antimicrobial TSNPs are formulated for processing within biodegradable biopolymers. Histone H5 AMP was selected for its reported strong antimicrobial action and functionalized with the TSNP (AMP-TSNP) in a similar fashion to previously reported TSNP biofunctionalisation methods. A synergy between the propensity of biopolymers for degradation and Ag+ release combined with AMP activity provides a novel mechanism for the sustained antimicrobial action of biopolymeric thin films. Nanoplates are transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. Extrusion is used in combination with calendering rolls to create thin polymerc film where the nanoplates are embedded onto the surface. The resultant antibacterial functional films are suitable to be adapted for food packing and biomedical applications. TSNP synthesis were synthesized by adapting a previously reported seed mediated approach. TSNP synthesis was scaled up for litre scale batch production and subsequently concentrated to 43 ppm using thermally controlled H2O removal. Nanoplates were transferred from aqueous phase to an organic solvent in order to facilitate integration within hydrophobic polymers. This was acomplised by functionalizing the TSNP with thiol terminated polyethylene glycol and using centrifugal force to transfer them to chloroform. Polycaprolactone (PCL) and Polylactic acid (PLA) were individually processed through extrusion, TSNP and AMP-TSNP solutions were sprayed onto the polymer immediately after exiting the dye. Calendering rolls were used to disperse and incorporate TSNP and TSNP-AMP onto the surface of the extruded films. Observation of the characteristic blue colour confirms the integrity of the TSNP within the films. Antimicrobial tests were performed by incubating Gram + and Gram – strains with treated and non-treated films, to evaluate if bacterial growth was reduced due to the presence of the TSNP. The resulting films successfully incorporated TSNP and AMP-TSNP. Reduced bacterial growth was observed for both Gram + and Gram – strains for both TSNP and AMP-TSNP compared with untreated films indicating antimicrobial action. The largest growth reduction was observed for AMP-TSNP treated films demonstrating the additional antimicrobial activity due to the presence of the AMPs. The potential of this technology to impede bacterial activity in food industry and medical surfaces will forge new confidence in the battle against antibiotic resistant bacteria, serving to greatly inhibit infections and facilitate patient recovery.

Keywords: antimicrobial, biodegradable, peptide, polymer, nanoparticle

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Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud

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A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.

Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique

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Authors: Sulaiman A. Alrumman, Abd El-Latif Hesham

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Despite medical progress worldwide, dental caries are still widespread. Miswak is derived from the plant arak (Salvadora persica). It is used by Muslim people as a natural product for the cleansing of teeth, to ensure oral and dental hygiene. This study was designed to evaluate the antimicrobial effects of ethanol, methanol, and ethanol/methanol extracts of miswak against three bacterial pathogens of the oral cavity. The pathogens were isolated from the oral cavity of volunteers/patients and were identified on the basis of 16S rRNA gene amplification data. Sequence comparisons were made with 16S rRNA gene sequences available in the GenBank database. The results of sequence alignment and phylogenetic analysis identified the three pathogens as being Staphylococcus aureus strain KKU-020, Enterococcus faecalis strain KKU-021 and Klebsiella pneumoniae strain KKU-022. All miswak extracts showed powerful antimicrobial activity against the three pathogens. The maximum zone of inhibition (40.67±0.88 mm) was observed against E. faecalis with ethanolic extracts whilst methanolic extracts showed the minimum zone of inhibition (10.33±0.88 mm) against K. pneumonia KKU-022. Based on the significant effects of the miswak extracts against the oral cavity pathogens in our study, we recommend that miswak is to be used as a dental hygiene method to prevent tooth caries.

Keywords: antibacterial, miswak, Salvadora persica, oral cavity pathogens

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Authors: Ndje Ndje Mireille

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The improvement in the physical aspects of hysterectomy has tended to make us forget the psychological burden of this operation for many women. African women closely associate fertility and femininity, and they fear that their desire will diminish, that they will be less desirable after having undergone a hysterectomy. Medicine may be tempted to trivialize this surgical intervention by relying on the evolution of current surgery that leaves little or no marks. It is possible to think that the uterus is useless for a nun who has decided to freely disregard her motherhood. We used the clinical research method for this study. Through a semi-directive interview guide, we collected the verbatims of an hysterectomized catholic nun. The verbatims were transcribed and analyzed with the thematic content analysis. This analysis shows that the medical reality does not always correspond to the subjective experience of women, for whom hysterectomy can imply strong symbolic damage. The uterus is not essential to life, but it is essential to give life, and this lack can reactivate a desire for motherhood. The experience of hysterectomy is unique for each woman in relation to her history. This operation will eliminate all hope of pregnancy; it will be felt as intimate mutilation and an attack on femininity, it will bring up concerns about sexuality. Even if a woman has past the age of having children, has gone through menopause, or has freely decided not to have children, she still find it difficult to accept this procedure. The lack of uterus make a woman feel useless.

Keywords: hysterectomy, symbolic damage, desire for motherhood, feminity, nun

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Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Lichung Jen, Yi Chun Liu, Kuan-Wei Lee

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Fruitful data has been accumulated in database nowadays and is commonly used as support for decision-making. In the healthcare industry, hospital, for instance, ordering pharmacy inventory is one of the key decision. With large drug inventory, the current cost increases and its expiration dates might lead to future issue, such as drug disposal and recycle. In contrast, underestimating demand of the pharmacy inventory, particularly standing drugs, affects the medical treatment and possibly hospital reputation. Prescription behaviour of hospital physicians is one of the critical factor influencing this decision, particularly irregular prescription behaviour. If a drug’s usage amount in the month is irregular and less than the regular usage, it may cause the trend of subsequent stockpiling. On the contrary, if a drug has been prescribed often than expected, it may result in insufficient inventory. We proposed a hierarchical Bayesian mixture model with two components to identify physicians’ regular/irregular prescription patterns with probabilities. Heterogeneity of hospital is considered in our proposed hierarchical Bayes model. The result suggested that modeling the prescription patterns of physician is beneficial for estimating the order quantity of medication and pharmacy inventory management of the hospital. Managerial implication and future research are discussed.

Keywords: hierarchical Bayesian model, poission mixture model, medicines prescription behavior, irregular behavior

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Authors: Fatemeh Nokhodchi Bonab

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Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 127

Authors: Yutong An

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Premature babies in the Neonatal Intensive Care Unit (NICU) are usually protected in individual incubators to ensure a constant temperature and humidity. Accompanied by 24-hour monitoring by medical equipment, this provides a considerable degree of protection for the growth of preterm babies. However, preterm babies are still continuously exposed to noise at excessively high decibels (>45dB). Such noise has a highly damaging effect on the growth and development of preterm babies. For example, in the short term, it can lead to sleep deprivation, stress reactions, and difficulty calming emotions, while in the long term, it can trigger endocrine disorders, metabolic disorders, and hearing impairment. Fortunately, musical interventions in the NICU have been shown to provide calmness to newborns. This article integrates existing research on three types of music that are beneficial for preterm infants and their respective advantages and disadvantages. This paper aims to present a possibility, based on existing NICU equipment and experimental data related to musical interventions, to reduce the impact of noise on preterm babies in the NICU through a system design approach that incorporates a personalized adjustable music system in the incubator and an overall music enhancement in the open bay of the NICU.

Keywords: music interventions, neonatal intensive care unit (NICU), premature babies, neonatal nursing

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Authors: Ahmad Shah Farhat

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Background: Prenatal asphyxia or birth asphyxia is the medical situation resulting from a newborn infant that lasts long enough during the birth process to cause physical harm, usually to the brain. Human umbilical cord blood (UCB) is a well-established source of hematopoietic stem/progenitor cells (HSPCs) for allogeneic stem cell transplantation. These can be used clinically to care for children with malignant diseases. Low O2 can cause in proliferation and differentiation of stem cells. Method: the cord blood of 11 infants with 3-5 Apgar scores or need to cardiac pulmonary Resuscitation as an asphyxia group and ten normal infants with more than 8 Apgar scores as the normal group was collected, and after isolating hematopoietic stem cells, the cells were cultured in enriched media for 14 days to compare the numbers of colonies by microscope. Results: There was a significant difference in the number of RBC precursor colonies (red colonies) in cultured media with 107 cord blood hematopoietic stem cells of infants who were exposed to hypoxemia in two wells of palate. There was not a significant difference in the number of white cell colonies in the two groups in the two wells of the plate. Conclusion: Hypoxia in the perinatal period can cause the increase of hematopoietic stem cells of cord blood, special red precursor stem cells in vitro, like an increase of red blood cells in the body when exposed to low oxygen conditions. Thus, it will be usable.

Keywords: asphyxia, neonre, stem cell, red cell

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Authors: Muhammad Naziru Yahaya, Buhari Samaila, Nasiru Abubakar

Abstract:

Noise pollution caused by vehicular movement in urban cities has reached alarming proportions due to continuous increases in vehicles and industrialization. Traffic noise causes deafness, annoyance, and other health challenges. According to World Health Organization recommends 60Db daytime sound levels and 40db night time sound levels in hospitals, schools, and other residential areas. Measurements of traffic noise were taken at six different locations of selected healthcare facilities at Birnin Kebbi (Sir Yahaya Memorial Hospital and Federal Medical Centre Birnin Kebbi). The data was collected in the vicinity of hospitals using the slow setting of the device and pointed at noise sources. An integrated multifunctional sound level GM1352, KK2821163 model, was used for measuring the emitted noise and temperatures. The data was measured and recorded at three different periods of the day 8 am – 12 pm, 3 pm – 6 pm, and 6 pm – 8:30 pm, respectively. The results show that a fair traffic flow producing an average sound level in the order of 38db – 64db was recorded at GOPDF, amenityF, and ante-natalF. Similarly, high traffic noise was observed at GOPDS, amenityS, and Fati-LamiS in the order of 52db – 78db unsatisfactory threshold for human hearing.

Keywords: amenities, healthcare, noise, hospital, traffic

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Authors: Ibrahim A. Alkali

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There is no reservation on the outstanding contribution of patient families in restoration of hospitalised patients, hence their consideration as essential component of hospital ward regimen. The psychological and emotional support a patient requires has been found to be solely provided by the patient’s family. However, consideration of their presence as one of the major functional requirements of an inpatient setting design have always been a source of disquiet, especially in developing countries where policies, norms and protocols of healthcare administration have no consideration for the patients’ family. This have been a major challenge to the hospital ward facilities, a concern for the hospital administration and patient management. The study therefore is aimed at obtaining a consensus opinion on the best approach for family integration in the design of an inpatient setting.  A one day visioning charrette involving Architects, Nurses, Medical Doctors, Healthcare assistants and representatives from the Patient families was conducted with the aim of arriving at a consensus opinion on practical design approach for sustainable family integration. Patient’s family are found to be decisive character of hospital ward regimen that cannot be undermined. However, several challenges that impede family integration were identified and subsequently a recommendation for an ideal approach. This will serve as a guide to both architects and hospital management in implementing much desired Patient and Family Centred Care.

Keywords: patient's family, inpatient setting, care giving, integration

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Authors: Michal Natan, Ori Gutman, Shlomo Margel, Ehud Banin

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Biofilm formation is a serious problem in medical and industrial settings due to the increased resistance of these communities to killing compared to free-living bacteria. This has prompted the search for agents that can inhibit both bacterial growth and biofilm formation. In this study, N-halamine rechargeable nanoparticles (NPs) were synthesized by co-polymerization of the monomer methacryl amide and the cross-linker monomer N,N-methylene bisacryl amide, and were subsequently loaded with Cl+, using bleach. The chlorinated NPs exhibited remarkable stability to organic reagents. The antibacterial mechanism of the P(MAA-MBAA)-Cl NPs involved generation of reactive oxygen species (ROS) only upon exposure to organic media, but not upon incubation in water, suggesting a specific activation. Moreover, a unique interaction of the P(MAA-MBAA)-Cl NPs with Staphylococcus aureus bacteria but not with human cells was discovered, whereby these microorganisms were all specifically targeted and marked for destruction. Finally, in collaboration with Netafim Ltd. irrigation drippers containing the P(MAA-MBAA)-Cl were incubated in the field and were shown to prevent fouling on them for 5 months as opposed to the control drippers that exhibited substantial fouling. Further, the NPs offer recharging to the surface, thus providing long-lasting protection that does not exist in the products available today. Taken together, the results demonstrate the great potential of implementing the charged NPs in devices and surfaces to prevent bacterial growth.

Keywords: bacteria, biofilm, fouling, nanoparticles

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Authors: Adisu Mengesha Assefa

Abstract:

The field of cardiovascular care is being transformed by the incorporation of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), collectively known as Extended Reality (XR), into medical education, procedural planning, and patient care. This review examines the state-of-the-art applications of XR in cardiology, emphasizing its role in enhancing the precision of interventional procedures and understanding complex anatomical structures. XR technologies complement conventional imaging methods by enabling immersive three-dimensional interaction that facilitates both preoperative planning and intraoperative guidance. Despite these promising developments, challenges such as harmonizing data, integrating various imaging systems, and addressing the prevalence of cybersickness remain. Ethical considerations, including maintaining physician focus and ensuring patient safety, are crucial when implementing XR in clinical settings. This review summarizes the existing literature and highlights the need for more rigorous future studies to validate therapeutic benefits and ensure safe application. By examining both the potential and the challenges, this paper aims to delineate the current and future roles of XR in cardiovascular care, emphasizing the necessity for continued innovation and ethical oversight to improve patient outcomes.

Keywords: virtual reality, augmented reality, mixed reality, cardiovascular care, education, preprocedural planning, intraoperative guidance, postoperative patient rehabilitation

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Authors: Syue-Liang Lin, C. Allen Chang

Abstract:

Luminescence imaging is an important technique used in biomedical research and clinical diagnostic applications in recent years. Concurrently, the development of NIR luminescence probes / imaging contrast agents has helped the understanding of the structural and functional properties of cells and animals. Photodynamic therapy (PDT) is used clinically to treat a wide range of medical conditions, but the therapeutic efficacy of general PDT for deeper tumor was limited by the penetration of excitation source. The tumor targeting biomedical nanomaterials UCNP@PS (upconversion nanoparticle conjugated with photosensitizer) for photodynamic therapy and near-infrared imaging of cancer will be developed in our study. Synthesis and characterization of biomedical nanomaterials were completed in this studies. The spectrum of UCNP was characterized by photoluminescence spectroscopy and the morphology was characterized by Transmission Electron Microscope (TEM). TEM and XRD analyses indicated that these nanoparticles are about 20~50 nm with hexagonal phase. NaYF₄:Ln³⁺ (Ln= Yb, Nd, Er) upconversion nanoparticles (UCNPs) with core / shell structure, synthesized by thermal decomposition method in 300°C, have the ability to emit visible light (upconversion: 540 nm, 660 nm) and near-infrared with longer wavelength (downconversion: NIR: 980 nm, 1525 nm) by absorbing 800 nm NIR laser. The information obtained from these studies would be very useful for applications of these nanomaterials for bio-luminescence imaging and photodynamic therapy of deep tumor tissue in the future.

Keywords: Near Infrared (NIR), lanthanide, core-shell structure, upconversion, theranostics

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Authors: Ramazan Bakir, Gizem Kayar

Abstract:

It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

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Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

Abstract:

Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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