Información de la Revista

Computers in Biology and Medicine

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Factor de Impacto:
6.3
Editor:
Elsevier
ISSN:
0010-4825
Vistas:
25289
Seguidores:
6

Solicitud de Artículos

Computers in Biology and Medicine is an academic journal published by Elsevier. (ISSN 0010-4825, impact factor 6.3).

Computers in Biology and Medicine, a companion title to Informatics in Medicine Unlocked, is a medium of international communication of the revolutionary advances being made in the application of the computer to the fields of bioscience and medicine. The Journal will focus on such areas as: Analysis of Biomedical Systems: Solutions of Equations Synthesis of Biomedical Systems: Simulations Special Medical Data Processing Methods Special Purpose Computers Clinical Data Processing for Real Time Clinical and Experimental Use Medical Diagnosis and Medical Record Processing Biomedical Engineering Medical Informatics Bioinformatics Medical Applications of the Internet and World Wide Web Human Genomics Proteomics Functional Brain Studies Articles which examine the following topics of special interest are being featured in Computers in Biology and Medicine: computer aids to the analysis of biochemical systems, computer aids to biocontrol-systems engineering, neuronal simulation by digital-computer gating components, automatic computer analysis of pictures of biological and medical importance, use of computers by commercial pharmaceutical and chemical organizations, radiation-dosage computers, and accumulating and recalling individual medical records, real-time languages, interfaces to patient monitors, clinical chemistry equipment, data handling and display in nuclear medicine and therapy. CBM does not consider submissions: -describing research using fundamental in silico tools, like basic molecular docking not supported by detailed molecular dynamic simulations, post modelling/dynamics analysis, estimation and mathematical modelling and advanced algorithmic treatment with the data sets, or by detailed experimental validations. -with unclear dataset division into training/validation/test sets and/or imprecise downstream task analysis, specifically for image segmentation papers. -with minor architecture/model modifications and only slight increase in performance validation parameters (accuracy, Dice, etc) and/or lack of comparison with real state-of-the-art methods.
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