Search results for: personalized medicine

Authors: Meimei Zheng

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Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness.

Keywords: demand forecast updating, limited capacity, personalized products, optimization

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Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

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Authors: Farman Ali, Asif Mahmood

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The utilization of genetic markers in prostate cancer management represents a significant advance in personalized medicine, offering the potential for more precise diagnosis and tailored treatment strategies. This paper explores the pivotal role of genetic markers in the diagnosis and treatment of prostate cancer, emphasizing their contribution to the identification of individual risk profiles, tumor aggressiveness, and response to therapy. By integrating current research findings, we discuss the application of genetic markers in developing targeted therapies and the implications for patient outcomes. Despite the promising advancements, challenges such as accessibility, cost, and the need for further validation in diverse populations remain. The paper concludes with an outlook on future directions, underscoring the importance of genetic markers in revolutionizing prostate cancer care.

Keywords: prostate cancer, genetic markers, personalized medicine, BRCA1 and BRCA2

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Authors: Fangying Wang, Zhang Sanming, Ni Qian

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In recent years, more and more personalized sound absorbing materials have entered the Chinese room acoustical decoration market. The acoustic performance of three kinds of personalized sound-absorbing materials: Flame-retardant Flax Fiber Sound-absorbing Cotton, Eco-Friendly Sand Acoustic Panel and Transparent Micro-perforated Panel (Film) are tested by Reverberation Room Method. The sound absorption characteristic curves show that their performance match for or even exceed the traditional sound absorbing material. Through the application in the actual projects, these personalized sound-absorbing materials also proved their sound absorption ability and unique decorative effect.

Keywords: acoustic performance, application prospect personalized sound-absorbing materials

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: Vijay Kumar Kutala, Addepalli Pavani, M. Amresh Rao, Naushad Sm

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In this study, we evaluated the impact of CYP2C9*2 and CYP2C9*3 variants on binding and hydroxylation of warfarin. In silico data revealed that warfarin forms two hydrogen bonds with protein backbone i.e. I205 and S209, one hydrogen bond with protein side chain i.e. T301 and stacking interaction with F100 in CYP2C9*1. In CYP2C9*2 and CYP2C9*3 variants, two hydrogen bonds with protein backbone are disrupted. In double variant, all the hydrogen bonds are disrupted. The distances between C7 of S-warfarin and Fe-O in CYP2C9*1, CYP2C9*2, CYP2C9*3 and CYP2C9*2/*3 were 5.81A°, 7.02A°, 7.43° and 10.07°, respectively. The glide scores (Kcal/mol) were -7.698, -7.380, -6.821 and -6.986, respectively. Increase in warfarin/7-hydroxy warfarin ratio was observed with increase in variant alleles. To conclude, CYP2C9*2 and CYP2C9*3 variants result in disruption of hydrogen bonding interactions with warfarin and longer distance between C7 and Fe-O thus impairing warfarin 7-hydroxylation due to lower binding affinity of warfarin.

Keywords: warfarin, CYP2C9 polymorphism, personalized medicine, in Silico

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Authors: Andy Wang

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Personalized learning refers to an educational approach that tailors instruction to meet the unique needs, interests, and abilities of each learner. This method of learning aims at providing students with a customized learning experience that is more engaging, interactive, and relevant to their personal lives. With generative AI technology, the author has developed a Personal Tutoring Bot (PTB) that supports personalized learning. The author is currently testing PTB in his EE 499 – Microelectronics Metrology course. Virtual Reality (VR) and Augmented Reality (AR) provide interactive and immersive learning environments that can engage student in online learning. This paper presents the rationale of integrating VR/AR tools in PTB and discusses challenges and solutions of incorporating VA/AR into the Personal Tutoring Bot (PTB).

Keywords: personalized learning, online education, hands-on practice, VR/AR tools

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Authors: Veronika Lesáková, Silvia Slezáková, František Štěpánek

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Additive manufacturing technologies producing drug dosage forms aimed at personalized medicine applications are promising strategies with several advantages over the conventional production methods. One of the emerging technologies is 3D printing which reduces manufacturing steps and thus allows a significant drop in expenses. A decrease in material consumption is also a highly impactful benefit as the tested drugs are frequently expensive substances. In addition, 3D printed dosage forms enable increased patient compliance and prevent misdosing as the dosage forms are carefully designed according to the patient’s needs. The incorporation of multiple drugs into a single dosage form further increases the degree of personalization. Our research focuses on the development of 3D printed tablets incorporating multiple drugs (candesartan, losartan) and thermoplastic polymers (e.g., KlucelTM HPC EF). The filaments, an essential feed material for 3D printing,wereproduced via hot-melt extrusion. Subsequently, the extruded filaments of various formulations were 3D printed into tablets using an FDM 3D printer. Then, we have assessed the influence of the internal structure of 3D printed tablets and formulation on dissolution behaviour by obtaining the dissolution profiles of drugs present in the 3D printed tablets. In conclusion, we have developed tablets containing multiple drugs providing modified release profiles. The 3D printing experiments demonstrate the high tunability of 3D printing as each tablet compartment is constructed with a different formulation. Overall, the results suggest that the 3D printing technology is a promising manufacturing approach to dual tablet preparation for personalized medicine.

Keywords: 3D printing, drug delivery, hot-melt extrusion, dissolution kinetics

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Authors: Hamsa T. Tayeb, Mohammad A. Arafah, Dana M. Bakheet, Duaa M. Khalaf, Agnieszka Tarnoska, Nduna Dzimiri

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Background: CYP2D6 is a member of the cytochrome P450 mixed-function oxidase system. The enzyme is responsible for the metabolism and elimination of approximately 25% of clinically used drugs, especially in breast cancer and psychiatric therapy. Different phenotypes have been described displaying alleles that lead to a complete loss of enzyme activity, reduced function (poor metabolizers – PM), hyperfunctionality (ultrarapid metabolizers–UM) and therefore drug intoxication or loss of drug effect. The prevalence of these variants may vary among different ethnic groups. Furthermore, the xTAG system has been developed to categorized all patients into different groups based on their CYP2D6 substrate metabolization. Aim of the study: To determine the prevalence of the different CYP2D6 variants in our population, and to evaluate their clinical relevance in personalized medicine. Methodology: We used the Luminex xMAP genotyping system to sequence 305 Saudi individuals visiting the Blood Bank of our Institution and determine which polymorphisms of CYP2D6 gene are prevalent in our region. Results: xTAG genotyping showed that 36.72% (112 out of 305 individuals) carried the CYP2D6_*2. Out of the 112 individuals with the *2 SNP, 6.23% had multiple copies of *2 SNP (19 individuals out of 305 individuals), resulting in an UM phenotype. About 33.44% carried the CYP2D6_*41, which leads to decreased activity of the CYP2D6 enzyme. 19.67% had the wild-type alleles and thus had normal enzyme function. Furthermore, 15.74% carried the CYP2D6_*4, which is the most common nonfunctional form of the CYP2D6 enzyme worldwide. 6.56% carried the CYP2D6_*17, resulting in decreased enzyme activity. Approximately 5.73% carried the CYP2D6_*10, consequently decreasing the enzyme activity, resulting in a PM phenotype. 2.30% carried the CYP2D6_*29, leading to decreased metabolic activity of the enzyme, and 2.30% carried the CYP2D6_*35, resulting in an UM phenotype, 1.64% had a whole-gene deletion CYP2D6_*5, thus resulting in the loss of CYP2D6 enzyme production, 0.66% carried the CYP2D6_*6 variant. One individual carried the CYP2D6_*3(B), producing an inactive form of the enzyme, which leads to decrease of enzyme activity, resulting in a PM phenotype. Finally, one individual carried the CYP2D6_*9, which decreases the enzyme activity. Conclusions: Our study demonstrates that different CYP2D6 variants are highly prevalent in ethnic Saudi Arabs. This finding sets a basis for informed genotyping for these variants in personalized medicine. The study also suggests that xTAG is an appropriate procedure for genotyping the CYP2D6 variants in personalized medicine.

Keywords: CYP2D6, hormonal breast cancer, pharmacogenetics, polymorphism, psychiatric treatment, Saudi population

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Zoe Wong

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The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

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Authors: Xinyu Gong, Zhilin Li, Xintao Liu

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Maps are a means of communication. Cartographic language involves established theories of natural language for understanding maps. “Cartographic words’, or “map symbols”, are crucial elements of cartographic language. Personalized mapping is increasingly popular, with growing demands for customized map-making by the general public. Automated symbol-making and customization play a key role in personalized mapping. However, formal representations for the automated construction of map symbols are still lacking. In natural language, the process of word and sentence construction can be formalized. Through the analogy between natural language and graphical language, formal representations of natural language construction can be used as a reference for constructing cartographic language. We selected Chinese character structures (i.e., S

Keywords: personalized mapping, Chinese character, cartographic language, map symbols

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Authors: Hüseyin Biçer

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The purpose of this study is an explanation of using and expectation traditional and complementary medicine in Turkey in terms of regionally, cultural and social. Due to geopolitics position, at the intersection of the Middle East, Africa and Europe, Turkey has historically hosted many civilizations and cultures, and hosts many religions at the same time and therefore is very open to intercultural interaction. For this reason, the traditional medicine of Turkey contains traces of many civilizations rather than a traditional medicine of its own. In Turkey, complementary and traditional medicine are used actively. The aim of the study is to measure whether the patients have ever taken traditional medicine as a caretaker or for the supportive treatment of their diseases, and as a result, their expectations. This cross-sectional, paper-based survey study was conducted in 27 state hospitals and 29 family medicine clinics in seven geographical regions of Turkey. Patients who had an appointment in the waiting rooms that day were included. 77.4% of the patients participating in the study stated that they used traditional medicine at least 5 times in their life, 27.6% stated that traditional medicine was sufficient in some diseases, and 36.8% stated that traditional treatment was a part of normal treatment. Both faith and cultural approaches in Turkey always keep traditional medicine close to drugs. Another danger, apart from traditional medicine drugs that can interact with drugs, is that patients find it sufficient to use traditional and complementary medicine alone.

Keywords: complementary medicine, traditional medicine, medicine in Turkey, alternative medicine

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Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah

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Personalized learning becomes increasingly popular which not is restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability. The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT, it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores. Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.

Keywords: assessment, item response theory, cognitive load theory, learning, motivation, performance

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Authors: Ruthanne Tobin

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The shift to a personalized learning (PL) curriculum in Canada represents an innovative approach to teaching and learning that is also evident in various initiatives across the 32-nation OECD. The premise behind PL is that empowering individual learners to have more input into how they access and construct knowledge, and express their understanding of it, will result in more meaningful school experiences and academic success. In this paper presentation, the author reports on a document analysis of the new curriculum in the province of British Columbia. Three theoretical frameworks are used to analyze the new curriculum. Framework 1 focuses on five dominant aspects (FDA) of PL at the classroom level. Framework 2 focuses on conceptualizing and enacting personalized learning (CEPL) within three spheres of influence. Framework 3 focuses on the integration of three types of knowledge (content, technological, and pedagogical). Analysis is ongoing, but preliminary findings suggest that the new curriculum addresses framework 1 quite well, which identifies five areas of personalized learning: 1) assessment for learning; 2) effective teaching and learning; 3) curriculum entitlement (choice); 4) school organization; and 5) “beyond the classroom walls” (learning in the community). Framework 2 appears to be less well developed in the new curriculum. This framework speaks to the dynamics of PL within three spheres of interaction: 1) nested agency, comprised of overarching constraints [and enablers] from policy makers, school administrators and community; 2) relational agency, which refers to a capacity for professionals to develop a network of expertise to serve shared goals; and 3) students’ personalized learning experience, which integrates differentiation with self-regulation strategies. Framework 3 appears to be well executed in the new PL curriculum, as it employs the theoretical model of technological, pedagogical content knowledge (TPACK) in which there are three interdependent bodies of knowledge. Notable within this framework is the emphasis on the pairing of technologies with excellent pedagogies to significantly assist students and teachers. This work will be of high relevance to educators interested in innovative school reform.

Keywords: curriculum reform, K-12 school change, innovations in education, personalized learning

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Authors: Matthew I. Bellgard

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The field of bioinformatics has made, and continues to make, substantial progress and contributions to life science research and development. However, this paper contends that a systems approach integrates bioinformatics activities for any project in a defined manner. The application of critical control points in this bioinformatics systems approach may be useful to identify and evaluate points in a pathway where specified activity risk can be reduced, monitored and quality enhanced.

Keywords: bioinformatics, food security, personalized medicine, systems approach

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Authors: Sahar Rakhshan, Simonetta Geninatti Crich, Diego Alberti, Rachele Stefania

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The combination of imaging and therapeutic agents in the same smart nanoparticle is a promising option to perform a minimally invasive imaging guided therapy. In this study, Low density lipoproteins (LDL), one of the most attractive biodegradable and biocompatible nanoparticles, were used for the simultaneous delivery of Paclitaxel (PTX), a hydrophobic antitumour drug and an amphiphilic contrast agent, Gd-AAZTA-C17, in B16-F10 melanoma cell line. These cells overexpress LDL receptors, as assessed by Flow cytometry analysis. PTX and Gd-AAZTA-C17 loaded LDLs (LDL-PTX-Gd) have been prepared, characterized and their stability was assessed under 72 h incubation at 37 ◦C and compared to LDL loaded with Gd-AAZTA-C17 (LDL-Gd) and LDL-PTX. The cytotoxic effect of LDL-PTX-Gd was evaluated by MTT assay. The anti-tumour drug loaded into LDLs showed a significantly higher toxicity on B16-F10 cells with respect to the commercially available formulation Paclitaxel Kabi (PTX Kabi) used in clinical applications. It was possible to demonstrate a high uptake of LDL-Gd in B16-F10 cells. As a consequence of the high cell uptake, melanoma cells showed significantly high cytotoxic effect when incubated in the presence of PTX (LDL-PTX-Gd). Furthermore, B16-F10 have been used to perform Magnetic Resonance Imaging. By the analysis of the image signal intensity, it was possible to extrapolate the amount of internalized PTX indirectly by the decrease of relaxation times caused by Gd, proportional to its concentration. Finally, the treatment with PTX loaded LDL on B16-F10 tumour bearing mice resulted in a marked reduction of tumour growth compared to the administration of PTX Kabi alone. In conclusion, LDLs are selectively taken-up by tumour cells and can be successfully exploited for the selective delivery of Paclitaxel and imaging agents.

Keywords: low density lipoprotein, melanoma cell lines, MRI, paclitaxel, personalized medicine application, theragnostic System

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Authors: Lei Zhang, Tingting Xu, Jun He, Zhenyu Yan

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Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy.

Keywords: email marketing, email content, reinforcement learning, machine learning, Q-learning

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

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The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

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Authors: R.T.P. De Silva, T. K. Wijayasiriwardhane, B. Jayawardena

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Most people nowadays spend their time indoor environment. Because of that, a quality indoor environment needs for them. This study was conducted to identify how to improve indoor visual comfort using a personalized light system. Light intensity, light color, glare, and contrast are the main facts that affect visual comfort. The light intensity which needs to perform a task is changed according to the task. Using necessary light intensity and we can improve the visual comfort of occupants. The hue can affect the emotions of occupants. The preferred light colors and intensity change according to the occupant's age and gender. The research was conducted to identify is there any relationship between personalization and visual comfort. To validate this designed an Internet of Things-based reading light. This light can work according to the standard light levels and personalized light levels. It also can measure the current light intensity of the environment and maintain continuous light levels according to the task. The test was conducted by using 25 undergraduates, and 5school students, and 5 adults. The feedbacks are gathered using Post-occupancy evaluation (POE) techniques. Feedbacks are gathered in three steps, It was done without any light control, with standard light level, and with personalized light level Users had to spend 10 minutes under each condition. After finishing each step, collected their feedbacks. According to the result gathered, 94% of participants rated a personalized light system as comfort for them. The feedbacks show stay under continuous light level help to keep their concentrate. Future research can be conducted on how the color of indoor light can affect for indoor visual comfort of occupants using a personalized light system. Further proposed IoT based can improve to change the light colors according to the user's preference.

Keywords: indoor environment quality, internet of things based light system, post occupancy evaluation, visual comfort

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Authors: Valerie Yocco Rossi

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Objective: The author will share why differentiation is necessary for all classrooms as well as strategies for differentiating content, process, and product. Through learning how to differentiate, teachers will be able to create activities and assessments to meet the abilities, readiness levels, and interests of all learners. Content and Purpose: This work will focus on how to create a learning experience for students that recognizes their different interests, abilities, and readiness levels by differentiating content, process, and product. Likewise, the best learning environments allow for choice. Choice boards allow students to select tasks based on interests. There can be challenging and basic tasks to meet the needs of various abilities. Equally, rubrics allow for personalized and differentiated assessments based on readiness levels and cognitive abilities. The principals of DI help to create a classroom where all students are learning to the best of their abilities. Outcomes: After reviewing the work, readers will be able to (1) identify the benefits of differentiated instruction; (2) convert traditional learning activities to differentiated ones; (3) differentiate, writing-based assessments.

Keywords: differentiation, personalized learning, design, instructional strategies

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Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

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Authors: Okhee Woo

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Purpose: The aim of this study is to evaluate 2-year cumulative effective radiation dose and cumulative organ dose on regular follow-up computed tomography (CT) scans in patients with breast cancer and to establish personalized low-dose CT protocol. Methods and Materials: A retrospective study was performed on the patients with breast cancer who were diagnosed and managed consistently on the basis of routine breast cancer follow-up protocol between 2012-01 and 2016-06. Based on ICRP (International Commission on Radiological Protection) 103, the cumulative effective radiation doses of each patient for 2-year follow-up were analyzed using the commercial radiation management software (Radimetrics, Bayer healthcare). The personalized effective doses on each organ were analyzed in detail by the software-providing Monte Carlo simulation. Results: A total of 3822 CT scans on 490 patients was evaluated (age: 52.32±10.69). The mean scan number for each patient was 7.8±4.54. Each patient was exposed 95.54±63.24 mSv of radiation for 2 years. The cumulative CT radiation dose was significantly higher in patients with lymph node metastasis (p = 0.00). The HER-2 positive patients were more exposed to radiation compared to estrogen or progesterone receptor positive patient (p = 0.00). There was no difference in the cumulative effective radiation dose with different age groups. Conclusion: To acknowledge how much radiation exposed to a patient is a starting point of management of radiation exposure for patients with long-term CT follow-up. The precise and personalized protocol, as well as iterative reconstruction, may reduce hazard from unnecessary radiation exposure.

Keywords: computed tomography, breast cancer, effective radiation dose, cumulative organ dose

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Authors: Bilal Wajid, Erchin Serpedin

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The health industry is aiming towards personalized medicine. If the patient’s genome needs to be sequenced it is important that the entire analysis be completed quickly. This paper explores use of parallel computing to analyze very large sequences. Two cases have been considered. In the first case, the sequence is kept constant and the effect of increasing the number of MPI-based processes is evaluated in terms of execution time, speed and efficiency. In the second case the number of MPI-based processes have been kept constant whereas, the length of the sequence was increased.

Keywords: parallel computing, alignment, genome assembly, alignment

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Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Freddy Patricio Moncayo-Matute, Pablo Gerardo Peña-Tapia, Vázquez-Silva Efrén, Paúl Bolívar Torres-Jara, Diana Patricia Moya-Loaiza, Gabriela Abad-Farfán

Abstract:

This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure.

Keywords: surgical planning, additive manufacturing, rapid prototyping, fused deposition modeling, custom anatomical model

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Authors: Hossein Miri, Zhou YongQi, Chan Bormei-Suy

Abstract:

The development of advanced technologies and innovative solutions has opened up exciting new possibilities for revolutionizing healthcare systems. One such emerging concept is the use of virtual and holographic health information platforms that aim to provide interactive and personalized medical information to users. This paper provides a review of notable virtual and holographic health information platforms. It begins by highlighting the need for information visualization and 3D representation in healthcare. It then proceeds to provide background knowledge on information visualization and historical developments in 3D visualization technology. Additional domain knowledge concerning holography, holographic computing, and mixed reality is then introduced, followed by highlighting some of their common applications and use cases. After setting the scene and defining the context, the need and importance of virtual and holographic visualization in medicine are discussed. Subsequently, some of the current research areas and applications of digital holography and holographic technology are explored, alongside the importance and role of virtual and holographic visualization in genetics and genomics. An analysis of the key principles and concepts underlying virtual and holographic health information systems is presented, as well as their potential implications for healthcare are pointed out. The paper concludes by examining the most notable existing mixed-reality applications and systems that help doctors visualize diagnostic and genetic data and assist in patient education and communication. This paper is intended to be a valuable resource for researchers, developers, and healthcare professionals who are interested in the use of virtual and holographic technologies to improve healthcare.

Keywords: virtual, holographic, health information platform, personalized interactive medical information

Procedia PDF Downloads 54