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.