Technology, specifically artificial intelligence (AI) is gradually but progressively creeping into the health sector and it’s perhaps the one that has been revolutionised most in diagnosis and treatment. This review brings out discussions on the practices of AI technologies in medical, the pros and the cons. First of all, an endeavour is made to elucidate the meaning of the term AI and its utilization in the field of healthcare. The specific AI techniques are described comprehensively focusing on the machine learning, deep learning, and natural language processing methods to be used in the project The role of multiple types of data in AI includes the EHR, medical images, and genomics data. Self-diagnosis: AI is improving the diagnosis approaches in the radiology and pathology fields and predicting the early-stage disease with better results in most of the cases, and enhancing the identification of genetic diseases. As for treatment, the enhancement of the use of AI has had an impact on issues such as; Prescribing and recommending drugs according to the characteristics of the patients, smart drug administration and management, robotic surgeries and simulations. Discussions are made using concrete and successful implementation of AI in cancer, cardiovascular, neurological and infectious diseases for the purpose of elucidating particular results. This also has to do with the ethical and legal problems like who has the liability to determine in the instance of complicated problems, patients’ information discretion, data privacy, and other legalities. In this article, we briefly mention the prosaic matters of AI, which deals with the engineering aspects of establishing AI such as the aspect of data and the ways and means of checking them and the interdisciplinary character of it. Concerning future developments, additional technologies like AI and connected devices in the field of health care, interdisciplinary at national and international level as well as data sharing is emphasized. Thus. AI has a very great perspective in healthcare, particularly in diagnostics and treatment of diseases due to the probability of increasing the level of accuracy, efficacy, and personalization. Despite these, they are tangible objectives with major challenges and require cooperation between nations with proper handling of Artificial Intelligence to practice clinical medication.
Read full abstract