Shaban-Nejad Arash, Michalowski Martin (eds.) Precision Health and Medicine: A Digital Revolution in Healthcare

Springer, 2019. — 203 p. — (Studies in Computational Intelligence 843) — ISBN: 978-3-030-24408-8This book highlights the latest advances in the application of artificial intelligence to healthcare and medicine. It gathers selected papers presented at the 2019 Health Intelligence workshop, which was jointly held with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the central issues, challenges, and potential opportunities in the field, along with new research results.By addressing a wide range of practical applications, the book makes the emerging topics of digital health and precision medicine accessible to a broad readership. Further, it offers an essential source of information for scientists, researchers, students, industry professionals, national and international public health agencies, and NGOs interested in the theory and practice of digital and precision medicine and health, with an emphasis on risk factors in connection with disease prevention, diagnosis, and intervention.From Precision Medicine to Precision Health: A Full Angle from Diagnosis to Treatment and Prevention
Constructing Accurate Confidence Intervals When Aggregating Social Media Data for Public Health Monitoring
MCA-Based Rule Mining Enables Interpretable Inference in Clinical Psychiatry
Automatic Exercise Recognition with Machine Learning
Assessment of Word Embedding Techniques for Identification of Personal Experience Tweets Pertaining to Medication Uses
Using Machine Learning for Automatic Estimation of M. Smegmatis Cell Count from Fluorescence Microscopy Images
Dynamic Transfer Learning for Named Entity Recognition
Autism Spectrum Disorder’s Severity Prediction Model Using Utterance Features for Automatic Diagnosis Support
Explaining Multi-label Black-Box Classifiers for Health Applications
Large-Scale Dialog Corpus Towards Automatic Mental Disease Diagnosis
Spoken Dialogue Systems for Medication Management
Deep Visual Models for EEG of Mindfulness Meditation in a Workplace Setting
End-to-End Joint Entity Extraction and Negation Detection for Clinical Text
Highly Efficient Follicular Segmentation in Thyroid Cytopathological Whole Slide Image
Analysis of Team Medical Care Using Integrated Information from the Trajectories of and Conversations Among Medical Personnel
Guiding Public Health Policy by Using Grocery Transaction Data to Predict Demand for Unhealthy Beverages
Domain Adaptation for Human Fall Detection Using Wi-Fi Channel State Information
Evaluating Ensemble Learning Impact on Gene Selection for Automated Cancer Diagnosis
EpiRL: A Reinforcement Learning Agent to Facilitate Epistasis Detection
Practical Evaluation of Different Omics Data Integration Methods