Artificial Intelligence in Health Sector: Current Status and Future Perspectives
Phani Teja Nallamothu, Kimberly Morton Cuthrell
Abstract
The developing fields of artificial intelligence (AI)/ machine learning (ML) offer a significant potential to improve healthcare services. Many areas of clinical practice, scientific research, and healthcare management have included AI/ML techniques. Screening and daily fitness monitoring, diagnostic services in gastroenterology, pathology, and radiology, as well as support for clinical decision-making and palliative care, are the main categories involved. However, there are significant obstacles to the widespread use of AI/ML in healthcare, including higher installation and maintenance costs, potentially harmful medical mistakes, a lack of ethical frameworks for AI, unemployment, and reduced capacity building within the human workforce. Many business initiatives have now been created in the field of healthcare AI/ML innovation. They offer everything from advanced diagnostics to vitals monitoring in their products and services. In short, AI/ML may be extremely important in addressing the difficulties with complexity and the explosion of data in the healthcare system. AI/ML is a component of contemporary healthcare, and its further adoption is contingent on thoroughly addressing pertinent issues.