Artificial intelligence in medicine: its working, potentials and challenges
Keywords:Artificial intelligence, Neural networks, Machine learning, Deep learning, Biomedicine, Future of medicine
Artificial intelligence (AI) is the science and engineering of making intelligent machines to think and learn. The interest and involvement of AI in health care has expanded fast during the last decade. The use of AI based technologies has been integrated into medicine to raise the standard of patient care by accelerating processes and achieving greater accuracy in different clinical settings. The patient’s electronic records, pathology slides and different radiological images are nowadays assessed by AI technologies such as machine learning (ML) and deep learning (DL). This, in turn, has aided in the process of diagnosis and treatment of patients and increased physicians’ capabilities. AI is poised to transform medical practice in future. AI can aid clinicians to make accurate remedy choices, minimize needless surgeries, benefit oncologists to enhance patient’s chemotherapy regimen etc. The aim of this review is to primarily develop fundamental knowledge and awareness of AI among the healthcare professionals. The article mainly deals with the basic mechanism of AI, the recent scientific developments and applications of AI along with its risks and challenges in clinical setup.
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