TY - JFULL AU - Giovanni Luca Masala PY - 2007/3/ TI - Pattern Recognition Techniques Applied to Biomedical Patterns T2 - International Journal of Health and Medical Engineering SP - 112 EP - 121 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/2266 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 2, 2007 N2 - Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects. ER -