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This book provides a comprehensive summary on the ten years of research work by the authors in the field of computerized TCM data analysis. The book first presents a general introduction to computerized TCM data analysis (CTDA), and then briefly introduces the essential background on signal/image processing and pattern recognition. After that, this book looks into three main TCM data analysis technologies: computerized tongue analysis, computerized pulse analysis, and computerized odor analysis. Finally, conclusion and remarks are provided to give the authors' perspectives on ongoing and future research.
The introduction of traditional Chinese medicine (TCM) through modern information technology will not only achieve the objective progress of the heritage of thousands of years of TCM, but also deliver novel discoveries for modern medicines.This book is an advanced monograph based on a decade's worth of research work by the authors. After a brief introduction on the four diagnosis approaches in TCM, this book delves into the three main TCM data analysis techniques: computerized tongue, pulse and odor analysis.Both graduate students and researchers in computerized TCM data analysis will benefit from the book as it will provide a comprehensive understanding of the state-of-the-art analysis methods, image / signal acquisition devices, and the related feature extraction and classification methods.
Annotation This volume constitutes the refereed proceedings of the Second International Conference on Medical Biometrics, ICMB 2010, held in Hong Kong, China, in June 2010.
What features or information can we observe from a face, and how can these information help us to understand the person concerned, in terms of their well-being and what can we learn about and from each given feature? This book answers these questions by first dividing a face's multiple characteristics into two main categories: original (or physiological) features and features that change over a lifetime. The first category, original features, may be further divided into two sub-classes: features special (or unique) to an individual, and features common to a particular group. The second, changed features, can also be subdivided into two groups: features altered due to disease or features altered by other external factors. From these four sub-categories, four different applications — facial identification using original and special features; beauty analysis using original common features; facial diagnosis by disease changed features; and expression recognition through affect-changed features — are identified.The book will benefit researchers, professionals, and graduate students working in the field of computer vision, pattern recognition, security/clinical practice, and beauty analysis, and will also be useful for interdisciplinary research.
This book constitutes the refereed proceedings of the First International Conference on Medical Biometrics, ICMB 2008, held in Hong Kong, China. The 17 revised full papers and 23 revised poster papers were carefully reviewed and selected from numerous submissions. Medical biometrics is emerging as a very promising and reliable method for automated medical diagnosis. It integrates multidisciplinary technologies in biology, medicine, electronics, computing, and statistics.
This book constitutes the refereed proceedings of the First International Conference on Medical Biometrics, ICMB 2008, held in Hong Kong, China. The 17 revised full papers and 23 revised poster papers were carefully reviewed and selected from numerous submissions. Medical biometrics is emerging as a very promising and reliable method for automated medical diagnosis. It integrates multidisciplinary technologies in biology, medicine, electronics, computing, and statistics.
Biometrics-based authentication and identification are emerging as the most reliable method to authenticate and identify individuals. Biometrics requires that the person to be identified be physically present at the point-of-identification and relies on `something which you are or you do' to provide better security, increased efficiency, and improved accuracy. Automated biometrics deals with physiological or behavioral characteristics such as fingerprints, signature, palmprint, iris, hand, voice and face that can be used to authenticate a person's identity or establish an identity from a database. With rapid progress in electronic and Internet commerce, there is also a growing need to authenticate the identity of a person for secure transaction processing. Designing an automated biometrics system to handle large population identification, accuracy and reliability of authentication are challenging tasks. Currently, there are over ten different biometrics systems that are either widely used or under development. Some automated biometrics, such as fingerprint identification and speaker verification, have received considerable attention over the past 25 years, and some issues like face recognition and iris-based authentication have been studied extensively resulting in successful development of biometrics systems in commercial applications. However, very few books are exclusively devoted to such issues of automated biometrics. Automated Biometrics: Technologies and Systems systematically introduces the technologies and systems, and explores how to design the corresponding systems with in-depth discussion. The issues addressed in this book are highly relevant to many fundamental concerns of both researchers and practitioners of automated biometrics in computer and system security.
This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.
This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention plans or to allow medical professionals to access the patient’s current status. This book will be of value to all with an interest in this expanding field.