Machine learning and iot : a biological perspective /
edited by Shampa Sen, Leonid Datta and Sayak Mitra.
- First edition.
- 1 online resource (374 pages) : 165 illustrations
chapter 1 Machine Learning: A Powerful Tool for Biologists -- chapter 2 Mining and Analysis of Bioprocess Data -- chapter 3 Data Mining in Nutrigenomics -- chapter 4 Machine Learning in Metabolic Engineering -- chapter 5 Big Data and Transcriptomics -- chapter 6 Comparative Study of Predictive Models in Microbial-Induced Corrosion -- chapter 7 Application of Data Mining Techniques in Autoimmune Diseases Research and Treatment -- chapter 8 Data Mining Techniques in Imaging of Embryogenesis -- chapter 9 Machine Learning Approach to Overcome the Challenges in Theranostics: A Review -- chapter 10 Emotion Detection System -- chapter 11 Segmentation and Clinical Outcome Prediction in Brain Lesions -- chapter 12 Machine Learning Based Hospital-Acquired Infection Control System -- chapter 13 No Human Doctor: Learning of the Machine -- chapter 14 The IoT Revolution -- chapter 15 Healthcare IoT (H-IoT): Applications and Ethical Concerns -- chapter 16 Brain-Computer Interface -- chapter 17 IoT-Based Wearable Medical Devices -- chapter 18 People with Disabilities: The Helping Hand of IoT -- chapter 19 Smart Analytical Lab -- chapter 20 Crop and Animal Farming IoT (CAF-IoT).
This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.
9781351029940
Bioinformatics--methodology.
Biology--Data processing--methodology.
NATURE / Reference.
SCIENCE / Life Sciences / Biology.
SCIENCE / Life Sciences / General.
MEDICAL / Biotechnology.
MEDICAL / Hospital Administration & Care.
Bioprocess Data.
Brain Computer Interface.
Healthcare Iot.
Machine Learning.
Nutrigenomics.
Transcritomics.
QH324.2
570.285
chapter 1 Machine Learning: A Powerful Tool for Biologists -- chapter 2 Mining and Analysis of Bioprocess Data -- chapter 3 Data Mining in Nutrigenomics -- chapter 4 Machine Learning in Metabolic Engineering -- chapter 5 Big Data and Transcriptomics -- chapter 6 Comparative Study of Predictive Models in Microbial-Induced Corrosion -- chapter 7 Application of Data Mining Techniques in Autoimmune Diseases Research and Treatment -- chapter 8 Data Mining Techniques in Imaging of Embryogenesis -- chapter 9 Machine Learning Approach to Overcome the Challenges in Theranostics: A Review -- chapter 10 Emotion Detection System -- chapter 11 Segmentation and Clinical Outcome Prediction in Brain Lesions -- chapter 12 Machine Learning Based Hospital-Acquired Infection Control System -- chapter 13 No Human Doctor: Learning of the Machine -- chapter 14 The IoT Revolution -- chapter 15 Healthcare IoT (H-IoT): Applications and Ethical Concerns -- chapter 16 Brain-Computer Interface -- chapter 17 IoT-Based Wearable Medical Devices -- chapter 18 People with Disabilities: The Helping Hand of IoT -- chapter 19 Smart Analytical Lab -- chapter 20 Crop and Animal Farming IoT (CAF-IoT).
This book discusses some of the innumerable ways in which computational methods can be used to facilitate research in biology and medicine - from storing enormous amounts of biological data to solving complex biological problems and enhancing treatment of various grave diseases.
9781351029940
Bioinformatics--methodology.
Biology--Data processing--methodology.
NATURE / Reference.
SCIENCE / Life Sciences / Biology.
SCIENCE / Life Sciences / General.
MEDICAL / Biotechnology.
MEDICAL / Hospital Administration & Care.
Bioprocess Data.
Brain Computer Interface.
Healthcare Iot.
Machine Learning.
Nutrigenomics.
Transcritomics.
QH324.2
570.285