Methods and Models for Diagnosis and Prognosis in Medical Systems
1Universidad Carlos III de Madrid, P.O. Box 28911, Avenida de la Universidad 30, Leganés, Spain
2Division of Research and Postgraduate Studies, Technological Institute of Orizaba, Oriente 9 No. 82 Emiliano Zapata, Orizaba, VER, Mexico
3Bioinformatics at Centre for Plant Biotechnology and Genomics UPM-INIA, P.O. Box 28223, Science and Technology Park of UPM, Montegancedo Campus, Pozuelo de Alarcón, Madrid, Spain
4University of São Paulo, Instituto de Medicina Física e Reabilitação (IMREA), São Paulo, Brazil
Methods and Models for Diagnosis and Prognosis in Medical Systems
Description
During recent years, the development of medical systems (as part of clinical decision support systems (CDSSs)) has been one of the main research fields in biomedical informatics area. Different systems have been proposed to improve the quality of medical practice in several different areas such as pharmacy management, electronic health records, diagnosis systems, telemedicine, and medical imaging among others.
Several approaches and models have been developed since earliest 60's. Also several methods and techniques from the fields of artificial intelligence, decision theory and statistics have been introduced into models of the medical management of patients (diagnosis, treatment, and followup); in some of these models, assessment of the expected prognosis constitutes an integral part. Typically, recent prognostic methods rely on explicit (patho) physiological models, which may be combined with traditional models of life expectancy.
The main goals of this special issue is the publication of new algorithms and mathematical methods, decision theories, techniques and models based on probabilistic and quantitative approaches to solve existing or new issues. This special issue also aims to publish original research articles and reviews about the described field in some type of medical systems. Potential topics include, but are not limited to:
- Medical diagnosis systems
- Medical dosing systems
- Medical knowledge models and techniques
- Diagnosis and prognosis systems
- Mathematical predictive methods for medical diagnosis
- Statistics in diagnostic medicine
- Advanced soft computing diagnosis and prognosis models and methods
- Prognostic and diagnostic models in medical guidelines and protocols
- Evaluation of prognostic and diagnostic models
- Surveys about some of the aforementioned topics
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