The impact of machine learning on patient care: a systematic review

ConclusionThe majority of literature describing the use of ML in clinical medicine is retrospective in nature and often outlines proof-of-concept approaches to impact patient care. We postulate that identifying and overcoming key translational barriers, including real-time access to clinical data, data security, physician approval of “black box” generated results, and performance evaluation will allow for a fundamental shift in medical practice, where specialized tools will aid the healthcare team in providing better patient care.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research