Volume 2 | Issue 1 | 1 OA J Applied Sci Technol, 2024 Citation: Javanmard, S. (2024). Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare. OA J Applied Sci Technol, 2(1), 01-16. Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare * Corresponding Author Shahin Javanmard, Faculty of Medicine, Halic University, Türkiye. Submitted: 2023, Dec 13; Accepted: 2024, Jan 04; Published: 2024, Feb 19 Shahin Javanmard* Faculty of Medicine, Halic University, Türkiye Review Article Open Access Journal of Applied Science and Technology ISSN: 2993-5377 Abstract The twenty-first century has witnessed significant advancements in informatics, reshaping our understanding of data processing and accessibility. Artificial intelligence (AI), encompassing techniques such as machine learning (ML), deep learning (DP), and neural networks (NN), is poised to revolutionize medicine. AI holds the capability of analyzing vast amounts of data, extracting meaningful insights, and making accurate predictions, thereby empowering industries to make informed decisions, drive innovation, and enhance efficiency. The landscape of medical AI has evolved significantly, demonstrating expert-level disease detection from medical images and promising breakthroughs across various industries. AI revolutionizes medical practice by leveraging advanced algorithms and machine learning capabilities to improve diagnostics, treatment planning, and overall patient care. However, the deployment of medical AI systems in regular clinical practice still needs to be tapped, presenting complex ethical, technical, and human-centered challenges that must be addressed for successful implementation. While AI algorithms have shown efficacy in retrospective medical investigations, their translation into practical medical settings has been limited, raising concerns about their usability and interaction with healthcare professionals. Moreover, the representativeness of retrospective datasets in real-world medical practice is subject to filtering and cleaning biases. Integrating AI into clinical medicine holds great promise for transforming healthcare delivery, improving patient care, and revolutionizing aspects such as diagnosis, treatment planning, drug discovery, personalized treatment, and medical imaging. With advanced algorithms and machine learning capabilities, AI and robotics in Healthcare can analyze large volumes of medical data, extract meaningful insights, and provide accurate predictions, empowering healthcare professionals to make informed decisions and optimize resource allocation. The availability of extensive clinical, genomics, and digital imaging data, coupled with investments from healthcare institutions and technology giants, underscores the potential of AI in healthcare. This review article explores AI's powerful potential to revolutionize healthcare delivery across multiple domains, emphasizing the need to overcome challenges and harness its transformative capabilities in clinical practice. Keywords: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DP), Neural Networks (NN), Drug Discovery Personalized Treatment, Medical Imaging, AI & Robotics in Healthcare 1. Introduction As the century of technology progresses, the twenty-first century is distinguished by innovations in informatics that have fundamentally altered our understanding of data processing. Previously, the critical problem was acquiring access to information; however, in today's scientific community, fast- rising datasets are available at any time and can be quickly evaluated, shared, and kept in databases [1]. Innovations and New developments have increased human capabilities and hastened our scientific progress [2]. The phrase 'artificial intelligence'(AI), first used by John McCarthy in 1956, signifies the groundbreaking concept of simulating human intelligence in machines, revolutionizing various fields and paving the way for unprecedented technological advancements and problem- solving capabilities [3-5]. AI is set to revolutionize medicine in the coming years. The simulation of human intellect in computers is known as AI, and it includes techniques such as machine learning (ML), deep learning (DL), and neural networks (NN). The landscape of medical AI has evolved significantly since the initial breakthroughs, where algorithms demonstrated expert-level disease detection from medical images. AI is rapidly developing and can change a wide range of industries. Because of the intriguing possibilities given by AI, the subject of medical physics, in particular, has experienced a boom in research. DL, aided by large amounts of data and fast computers, propels tremendous advances in algorithmic innovation and neural solid network models. Thanks to the availability of promising learning methods and abundant computer resources, AI is on the verge of changing medical physics research and practices. As a result, our community must be ready for future challenges and possibilities and take the lead in this new period