Abstract

In the modern era, medical institutions offer patients high-quality, reasonably priced treatment, but they require sophisticated technology. But even with significant advancements in the computerization and digitalization of medicine, effective and reliable management solutions are still lacking. Medical operations are very complex, so high-level management is required. Machine learning techniques might be very useful in resolving these issues since they are scalable and adaptable to complex patterns. This study suggests that machine learning could improve human comprehension and oversight of healthcare operations, leading to more efficient healthcare delivery. The goal of the current study is to examine how machine learning methods can be used to detect diseases, various clinical trials, drug development, robotics-based surgery, organ image processing, and various challenges of machine learning in the medical industry. Finally, along with challenges, the study concludes that machine learning practices become essential for healthcare organizations of the modern era.