Deep learning techniques for biomedical and health informatics / 
edited by Basant Agarwal [and 4 others]. 
 - xv, 351 pages ;  24 cm. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/>Unified neural architecture for drug, disease, and clinical entity recognition -- Simulation on real time monitoring for user healthcare information -- Multimodality medical image retrieval using convolutional neural network -- A systematic approach for identification of tumor regions in the human brain through HARIS algorithm -- Development of a fuzzy decision support system to deal with uncertainties in working posture analysis using rapid upper limb assessment -- Short PCG classification based on deep learning -- Development of a laboratory medical algorithm for simultaneous detection and counting of erythrocytes and leukocytes in digital images of a blood smear -- Deep learning techniques for optimizing medical big data -- Simulation of biomedical signals and images using Monte Carlo methods for training of deep learning networks -- Deep learning-based histopathological image analysis for automated detection and staging of melanoma -- Potential proposal to improve data transmission in healthcare systems -- Transferable approach for cardiac disease classification using deep learning -- Automated neuroscience decision support framework -- Diabetes prediction using artificial neural network. 
<br/><br/><label>ISBN: </label>9780128190616 
<br/><br/><label>LCCN: </label>2019953930 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Medical informatics.<br/>Artificial intelligence--Medical applications.<br/>Machine learning.<br/>Medical informatics.<br/>Artificial intelligence--Medical applications.<br/>Machine learning.
<br/><br/><label>LC Class. No.: </label>R859.7.A78  / D433 2020 
<br/><br/><label>Dewey Class. No.: </label>610.285  / D360