In 2014, Larry Page, CEO's Google gave a talk at TED and one of the interesting ideas: is "What if everyone made their medical records available for scientists to research? Keep your personal identity anonymous, but give researchers the data. Page thinks we could save100,000 lives annually." Additionally, Health data has a wide variety of heterogeneous data sources which include medical literature, Electronic Medical Records (EMRs), medical imaging data, time series data from ICU/in-hospital sensors, insurance claims data, wearable sensors, mobile health applications data, clinical notes, imaging reports, patient narratives etc..

To serve a better of human-being, it requires inter-disciplinary research across multiple domains of computer and medical sciences. The goal of this workshop is to bring together researchers to discuss how data Mining and analytics methods can contribute to improving health quality and enhance data mining, text mining to work on problems from medicine and healthcare.

Topic areas for the workshop include (but are not limited to) the following:


Statistical analysis and characterization of healthcare data
Text mining - mining free text in electronic medical records
Visual analysis and exploration of longitudinal clinical trial data
Medical Information Search techniques
Data quality assessment and improvement: preprocessing, cleaning, missing data treatment etc.
Pattern detection and hypothesis generation from observational data
Smart health and big data
Natural language processing and text mining techniques for health data mining
Personal health apps, wearable and sensor data integration with traditional medical data