Artificial intelligence (AI) stands out as a potent asset across diverse industries, with its potential within the realm of medicine proving to be exceptionally profound. This chapter takes a comprehensive journey through the myriad applications of AI in healthcare, illuminating its profound influence on patient care, disease diagnosis, therapeutic interventions, and advanced medical exploration. The fusion of AI algorithms, machine learning paradigms, and deep learning strategies empowers healthcare providers to amplify operational efficiency, precision, and the very bedrock of decision-making processes. Within this document, an intricate examination of the merits and hurdles entailed in the integration of AI into the medical domain ensues, concurrently dissecting ethical quandaries and prospective trajectories for evolution.
Top2. Background
The realm of healthcare has borne witness to remarkable progressions across time, with technology emerging as a pivotal force in reshaping the landscape of patient care delivery. Amidst these transformative tides, the integration of Artificial Intelligence (AI) into the domain of medicine surfaces as an exceptionally ground-breaking stride. AI, a concept encapsulating the emulation of human cognition within machines, endows them with the prowess to undertake tasks traditionally requiring human intellect, encompassing facets like learning, reasoning, and intricate problem-solving.
The surge in AI's prominence and renown is attributed to its prowess in processing massive troves of data, identifying intricate patterns, and unearthing profound insights. Within the precincts of healthcare, AI harbors a profound potential to overhaul sundry dimensions, spanning the gamut from the expanse of medical imaging and diagnostics to the intricacies of devising treatment strategies and uncovering novel pharmaceutical compounds (Khang & Smart Healthcare, 2024).
Nurtured by the capabilities of machine learning algorithms and the intricate latticework of deep neural networks, AI holds within its grasp the means to augment the capacities of healthcare practitioners, resulting in elevated patient outcomes and more streamlined healthcare frameworks. The propulsion of AI into the medical sphere is propelled by the astronomical proliferation of medical data, encompassing electronic health archives, scans delineating medical imaging, and the strata of genomic information. The conventional manual methodologies of scrutinizing and construing these troves of data often transpire as laborious, susceptible to inaccuracies, and tinged with the biases inherent to human cognition. Herein, AI-driven systems manifest their potential, facilitating healthcare providers in expeditiously dissecting and parsing this colossal corpus of data with precision, celerity, and impartiality (Khang, Vugar and Abuzarova et al., 2023).