1Kemet Medical Consultants, USA
2PBJ Medical Associates, LLC, USA
3Independent Global Medical Research Consortium
4First InterHealth Group, Thailand
5Lakeline Wellness Center, USA
6Orange Partners Surgicenter, USA
7Chawla Health and Research, USA
8Cardiovascular and Thoracic Surgery Unit, Department of Surgery, Federal Medical Center, Umuahia, Nigeria
9Earthwide Surgical Missions, Nigeria
10Smart Wellness & Health Center, USA
11Lincolnshire Partnership NHS Foundation Trust, United Kingdom
12Northern Care Alliance NHS Foundation Trust, United Kingdom
13Adventhealth Tampa, USA
14Georgetown American University, Guayana
Artificial intelligence (AI) is an umbrella term that denotes the use of a computer to simulate intelligent behavior with minimal or no human involvement. AI implementation will significantly benefit the healthcare industry and people's general health. Although AI cannot wholly replace clinical judgment, it can help medical experts make better clinical decisions. AI unlocks new possibilities for learning, training, exploration, and development. Machine learning (ML) and deep learning (DL) are AI techniques for disease diagnosis, patient risk detection, and appropriate treatment options. Medical data from several sources, including ultrasonography, magnetic resonance imaging, mammography, genomics, computed tomography (CT), and positron emission tomography (PET), are essential to diagnose diseases using AI applications accurately. AI techniques diagnose major diseases in cancer, neurology, ophthalmology, gastroenterology, diabetology, and cardiology. AI has dramatically improved the hospital experience and accelerated patient preparation for home rehabilitation. Algorithm-based AI suggestions are highly systematic and eliminate human inconsistencies and errors. However, the sociological and ethical complexities of AI applications need more consideration, evidence of their economic and medical benefits, and the creation of multidisciplinary methods for their wider deployment. This review aims to investigate, summarize, and simplify AI's origin, development, types, uses (diagnosis and treatment), benefits (self-care, medical training, healthcare administration), limitations, and cost efficacy. It also discusses future perspectives and research on the use of AI in medical diagnosis and treatment.
Keywords: Algorithm-Based AI; Enhanced Hospital Experience; Enhancing Clinical Judgment; Diagnosis and Treatment; Machine Learning; Simulating Intelligent Behavior
Pruitt KD, Kerna NA, Carsrud NDV, Holets HM, Chawla S, Flores JV, Ngwu DC, Nnake I, Okeye UC, Azi CI, Olaleye KT, Nwachukwu D. "Artificial Intelligence: Applications and Effectiveness in the Healthcare Delivery System." EC Clinical and Medical Case Reports 6.7 (2023): 01-22.
© 2023 Pruitt KD, Kerna NA, Carsrud NDV, Holets HM, Chawla S, Flores JV, Ngwu DC, Nnake I, Okeye UC, Azi CI, Olaleye KT, Nwachukwu D. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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