The use of artificial intelligence in medicine first appeared in the 1790s. Notably, the first artificial intelligence machine learning methods were used to infer classification rules from labeled datasets, thereby assisting a knowledge-based decision support system. As a result, despite providing good patient care, the first system was not used on real patients (Hollis et al., 2019). These indicate that the machine was not linked to patients’ electronic health records and was instead considered a stand-alone system. Furthermore, the subjectivity expressed by the expert system’s knowledge bases was unacceptable, making it more suitable for teaching and limiting its application in clinical practice. As a result, the project will focus on the advantages of real improvements in healthcare through artificial intelligence.
In healthcare, artificial intelligence means an increase in the volume and complexity of data. Artificial intelligence is divided into three categories: life sciences companies, payers, and providers of care. Artificial intelligence in healthcare has the potential to transform many aspects of the healthcare administration process, including pharmaceuticals, payers, patient care, and providers. According to research, artificial intelligence can diagnose diseases better than humans in healthcare (Davenport & Kalakota, 2019). For example, using algorithms, artificial intelligence can help construct cohorts for costly clinical trials, outperforming the best radiologist at detecting malignant tumors.
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