Transforming Healthcare: Artificial Intelligence's Place in Contemporary Medicine - Shah Zeb; Nizamullah FNU; Nasrullah Abbasi; Muhammad Umer Qayyum (BULLET : Jurnal Multidisiplin Ilmu, 2024)
This review article explores the integration of artificial intelligence (AI) in healthcare, highlighting its potential benefits, challenges, and future directions. The main areas covered include AI's enhancement of diagnostic accuracy and efficiency in medical imaging by precision data analysis, thereby improving early detection and treatment outcomes. Notable examples of AI in action include Google's Deep Mind in retinal scans and IBM Watson Health in oncology. Artificial intelligence (AI) is revolutionizing healthcare by offering transformative advancements across various domains, from enhancing diagnostic accuracy to personalizing treatment strategies. Specific case studies illustrate the successful application of AI in various healthcare settings, including radiology, drug discovery, and patient monitoring. These examples highlight AI's impact on improving diagnostic precision, accelerating drug development, and enhancing patient care. AI accelerates drug discovery by analyzing complex biomedical data to identify potential drug candidates and predict their efficacy. Examples include Benevolent I’s work on ALS and Atom Wise’s efforts to identify Ebola antiviral compounds. AI improves patient monitoring through wearable devices and remote management systems, providing real-time insights and personalized recommendations. Examples include Fit bit’s health trackers and Living Health's chronic condition management platform. Better patient outcomes, optimized resource management, and enhanced operational efficiency are all made possible by artificial intelligence (AI). However, despite AI's potential, the healthcare industry faces a number of challenges related to the technology, including data privacy and security, bias and fairness in AI models, and integration with legacy systems. Resolving these issues is essential to the ethical and regulatory framework that governs the use of AI in healthcare. Important concerns include patient consent, accountability, transparency, and the development of appropriate regulations and standards.