Artificial Intelligence in Healthcare; Applications and Diagnostic Interpretations: A Literature Review.

Abstract

Background: Artificial intelligence (AI) is the most transformative technology of the 21st century and directs a new approach to shift healthcare through rapid advancement. It provides the path for clinicians to interpret the patient level in greater depth. Enthusiasm for applications of AI in healthcare has continued to grow. Objective: To provide a comprehensive understanding of the types and applications of AI in healthcare and diagnostic interpretations Methods: The review was performed systematically using the terms; “Artificial intelligence” AND “Healthcare” AND “Applications” AND “Diagnosis” from March 2024 to April 2024 on four databases; Google Scholar, Science Direct, PubMed, and Web of Science to identify the publications between 2015 and 2024. Results: Thirty-five articles were eligible from the initial search strategy of 2860 studies. Of these, nine definitions for AI were identified. AI is the imitation of human cognitive functions through several forms of computer software. Upon the organization of evidence, three types of AI; artificial neural networks including convolutional neural networks, machine learning, and modern deep learning were identified. Findings revealed that; digital consultation, robot-assisted surgery, patient interaction and chatbots, clinical trials, support evidence-based decision-making, drug development, and biomedical information processing as the applications of AI. Neurodegenerative disorders, cardio-vascular disease: progression, mortality and hospital stay, bladder volume, through medical image, cancer, epidemic, and psychiatric re-admission were identified as diagnostic interpretations. Conclusion: To identify the role of AI’s potential to enhance healthcare, careful design, implementation, and evaluation of AI-enabled systems will be important. Health ministries and hospital administration are recommended to enhance the utilization of AI in clinical practice to improve the quality of care. In the era of modern AI, healthcare workers need to be enriched with skills in applying AI techniques in the health field by engaging in training programs related to AI.