Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto?ML

Artificial Intelligence (AI) and machine learning (ML) have now spawned a new field within health care science research. These predictive analytics tools are starting to change various facets of our clinical domains including the practice laboratory medicine. Many these ML studies also populate literature landscape as we know it but unfamiliarity average reader basic knowledge critical concepts AI/ML is demanding need better prepare audience such relatively unfamiliar concepts. A fundamental platforms will inevitably enhance cross-disciplinary literacy ultimately lead enhanced integration understanding discipline. In this review, provide general outline along with an overview categories, specifically supervised, unsupervised, reinforcement learning. Additionally, since vast majority current approaches in medicine involve supervised algorithms, predominantly concentrate on platforms. Finally, for making more accessible investigator becoming major driving force automation This has given rise automated (Auto-ML) world which undoubtedly help shape future care. Hence, Auto-ML covered manuscript hopefully enrich reader's understanding, appreciation, embracing tools.