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Evolution of Clinical Medicine: From Expert Opinion to Artificial Intelligence
Antonio Barracca1, Mauro Contini2, Stefano Ledda3, Gianmaria Mancosu3, Giovanni Pintore4, Kianoush B Kashani5, Claudio Ronco6
1 abcGo Limited Liability Company (S.r.l), Cagliari, Italy
2 Machine Learning App Developer, Londra, Cagliari, Italy
3 Application Developer, Cagliari, Italy
4 Visual Computing Group, Sardinia Research Center 4 (CRS4), Sardegna, Italy
5 Department of Medicine, Division of Nephrology and Hypertension, Mayo Clinic; Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, USA
6 University of Padova, Padova; Department of Nephrology Dialysis & Transplantation, International Renal Research Institute (IRRIV), San Bortolo Hospital, Vicenza, Italy
Correspondence Address:
Prof. Kianoush B Kashani
Division of Nephrology and Hypertension, Mayo Clinic, 200 First Street SW, Rochester, Minnesota 55905
USA
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jtccm.jtccm_6_21
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Artificial intelligence provides a vast opportunity and conquest of the science of knowledge. Twenty-first-century medicine will be characterized by an extraordinary ability to access and process medical information to provide patient-specific, timely, and effective clinical decision support. The knowledge gained by patient care experience and clinicians' expertise has led to many clinical care advances. Access to a large volume of data, along with ever-growing information and knowledge of diseases, can allow us to optimize diagnoses and management strategies by using advances in machine learning and artificial intelligence. Changing the medical culture from only relying on the experts to use medical informatics advances to improve the experts' clinical judgment would be an uphill battle. It is necessary to overcome the clinicians' traditional training to empower them into moving in the data science, statistics, and artificial intelligence era. As the incorporation of artificial intelligence in clinical practice seems inevitable, a thorough understanding of its capacities and flaws is essential to the emergence of a new clinical practice world. This review paper describes some of the nuances of past, current, and future clinical decision support systems and artificial intelligence's impact on this process.
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