Editorial: Medical knowledge-assisted machine learning technologies in individualized medicine

Abstract

Machine learning (ML), a powerful tool for mining quantitative disease features in large quantities of medical data, is arguably the most important method for extracting, integrating, and modeling patient-specific and disease-specific factors for individualized medicine. ML can provide clinical decision support for disease diagnosis, prognosis, and treatment in practice. In reality, there is no universal ML model or solution for all medical problems and clinical circumstances, since both the fundamental biological mechanisms and the modality of the clinically interested medical data differ from disease to disease. In other words, biological and medical knowledge of the specific domain is essential for the development of ML models for the corresponding medical problems.

Feng GAO

Professor

My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.