Machine learning and iot : a biological perspective - Datta, Leonid; Sen, Shampa; Mitra, Sayak; Taylor and Francis (Boca Raton, FL : CRC Press, an imprint of Taylor and Francis, 2018)
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.
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).
Keywords: 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