MACHINE LEARNING, NATURAL LANGUAGE PROCESSING AND NETWORK ANALYSIS-GUIDED DISCOVERY RELATED TO MEDICAL RESEARCH

摘要

Techniques are disclosed for discovering, biological elements, functions and pathways, and environmental and nutritional factors related to diseases and medical syndromes. The techniques preprocess database query results and harmonize data using natural language processing before transforming them into the frequency space. The transformed results are analyzed with various categories of machine learning algorithms whose results are normalized, ranked and selectively combined, weighted or un-weighted, to produce a single result ranking the most important elements affecting a target disease or medical syndrome. The invention also uses alternative algorithms producing hypotheses on associations between medical topics, which are used as suggestions for exploratory medical research