Artificial Intelligence in Precision Health From Concept to Applications

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available.
This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health.

Info autore

Dr. Debmalya Barh is currently a Visiting Full Professor (Titular, Grade-E) in Bioinformatics and Precision Health at the Department of Genetics, Ecology, and Evolution, ICB, Federal University of Minas Gerais, Brazil and honorary scientist of the Institute of Integrative Omics and Applied Biotechnology (IIOAB), India. With over 20 years of experience, he has led academic, healthcare, molecular diagnostic, and bioinformatics industry endeavors. He works with more than 400 scientists from 100+ top ranked organizations across 40+ countries and has 220+ publications and a branded editor for 10+ cutting-edge omics related reference books. He is an expert in in precision/personalized health and integrative omics-based biomarker and target discovery in infectious and complex lifestyle diseases.

Dettagli sul prodotto

• Con la collaborazione di: Debmalya Barh (Editore), Barh Debmalya (Editore)
• Autori: Debmalya (EDT) Barh
• Editore: Academic Press London
• Contenuto: Libro
• Forma del prodotto: Tascabile
• Data pubblicazione: 04.03.2020
• Categoria: Scienze sociali, diritto, economia > Economia > Singoli rami economici, branche
• EAN: 9780128171332
• ISBN: 978-0-12-817133-2
• Numero di pagine: 500
• Categorie: Depression, Diabetes Mellitus, Big Data, machine learning, neurosurgery, Data Mining, Artificial Intelligence, Deep Learning, Healthcare, Surgery, Otorhinolaryngology, COMPUTER-AIDED DIAGNOSIS, diagnosis, MEDICAL / Biotechnology, biotechnology, Neural Networks, Personal & public health, Predictive Analysis, bipolar disorder, glioma, Natural Language Processing, Emergency Medicine, Ambient Assisted Living, Deep Neural Networks, Transmission, infectious diseases, heart failure, Data Warehouses, Personal and public health / health education, Medical Diagnosis, prognosis, Genomics, physical fitness, acute coronary syndrome, Neuro-Oncology, Patient Care, Myocardial infarction, Convolutional Neural Networks, Mortality, predictive modeling, telemedicine, expert systems, expert system, decision support systems, brain tumors, Prediction, Trusted AI, antibiotic resistance, precision health, health equity, Precision medicine, Artificial Neural Networks, Ambient Intelligence, Patient Monitoring, convolutional neural network, epidemics, Nutrition therapy, Clinical Decision Support Systems, Support Vector Machine (SVM), Explainability, drug repositioning, Clinical Informatics, Equity and Inclusion, Diabetes Management, Machine Learning Systems, Smart Health Care, spirometry, individual subject, nutrition assessment, Inclusion Body Myositis, Lung Function Tests, Type 1 diabetes mellitus, data-driven analytics, Big Data Science, Artificial neural network (ANN), coronary disease, Alzheimer’s disease detection, Machine learning techniques (MLT), Pathways analysis, Genetic risk scores, Diagnostic of respiratory diseases, Forced ­oscillation technique, Parametric finite element analysis, Clinical decision support ­analytics, Differential diagnosis generators, Nutritional surveillance, Phenotype prediction, Context aware notification, Clinical and translational research, Ensemble machine learning methods, Objective markers, Prediction of respiratory exacerbation