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Medical data processing and analysis
Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations.
Computational Life Sciences ; Vol. 3695 ; 1st International Symposium, CompLife 2005, Konstanz, Germany, September 25-27, 2005, Proceedings
This book constitutes the refereed proceedings of the First International Symposium on Computational Life Sciences, CompLife 2005, held in Konstanz, Germany in September 2005. The integration of knowledge in the life sciences is continuing apace with ev- increasingimportancebeing placedoncomputer-basedmethodsofdata capture, analysis, and knowledge representation. Today, our many di?erent sciences are providing us with a sea of information: it is the handling of this in?ux that is becoming a key discovery and regulatory question. The solutions to these problems will result in advancements to all of the involved sciences and will be highly in?uential both in the selection of the areas scientists seek to investigate and also on their success. For this to happen, it is crucial to establish an open and lively exchange between computer scientists, biologists, and chemists. To encourage precisely this type of exchange, crossing the borders of the sciences, we organized the 1st Symposium on Computational Life Science in Konstanz, Germany(September 25 27,2005).
Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
