WORLD JOURNAL OF ADVANCE
HEALTHCARE RESEARCH

Amar Saxena*, Shrestha Saxena, Yash Saxena, Ankit Kumar, Sanjeev Kumar, Prabhat Goyal, Chandrabhan Singh, Ashita Jain

ABSTRACT

Artificial Intelligence (AI) is turning the healthcare sector upside down, due to its ability to improve the analytical accuracy, treatment planning, and automate administrative work. The review therefore in detail covers the various functions of AI in a cross-sectional manner across various therapeutic topics, which include but are not limited to radiology, oncology, cardiology, gastroenterology, ophthalmology, and surgery. The research points to the paradigm shift that appliance learning (ML) and deep learning (DL) can have in the reading of compound medical statistics, speeding drug discovery and making long-term conservation personal. It also focuses on key initiatives including through confidentiality of data, algorithmic bias, principled governance, as well as clinical integration. As the number of submissions in image acknowledgement, predictive analytics, and virtual delivery of healthcare has been on the rise currently, AI has a tremendous potential to ensure that the existing gaps in healthcare systems all around the globe are attended to. Nevertheless, in order to be successfully implemented, it requires potent infrastructure, multi-disciplinary partnership, and constant verification so that the outcomes of healthcare are ethical, equitable, and reliable.