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Artificial Intelligence (AI) is transforming the healthcare landscape through the utilization of data analytics, automation, and machine learning methods to innovate patient care, operational effectiveness, and medical research. This paper delves into the complicated impact of AI in healthcare, emphasizing its influence on precision medicine, medical imaging, drug discovery, healthcare operations, and patient engagement. Within precision medicine, AI examines a variety of patient data, such as genetic details and medical backgrounds, to customize treatment strategies and enhance diagnostic precision. AI-driven medical imaging algorithms assist in the timely identification and diagnosis of illnesses like cancer and cardiovascular diseases, ultimately enhancing patient outcomes. Additionally, AI accelerates the drug discovery process by inspecting molecular configurations, forecasting drug interactions, and pinpointing potential candidates for clinical trials, thereby expediting therapeutic advancements. AI-powered solutions streamline healthcare operations by automating administrative duties, resource distribution, and workflow supervision, leading to enhanced efficiency and cost reduction. Remote patient monitoring via AI-enabled gadgets and wearables allows for continuous health monitoring, facilitating proactive management of chronic ailments and early diagnosis. The integration of Natural Language Processing (NLP) enables AI virtual assistants to engage with patients, arrange appointments, and extract insights from unstructured data such as electronic health records. Nevertheless, ethical and regulatory considerations, encompassing data privacy and bias mitigation, are critical in the integration of AI to ensure patient safety and trust.
Darna et al. (Sat,) studied this question.