International journal of surgery (London, England) · 2025
Transforming healthcare: the impact of artificial intelligence on diagnostics, pharmaceuticals, and ethical considerations - a comprehensive review.
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Deivayanai V C, Swaminaathanan Pavithra, Vickram A S, Saravanan A, Bibi Shabana, Aggarwal Navidha, Kumar Virender, Alhadrami Albaraa H, Mohammedsaleh Zuhair M, Altalhi Rawan, Nasser Bin-Jumah May, Sayed Amany A, Albaqami Amirah, Chopra Hitesh, Emran Talha Bin, Abdel-Daim Mohamed M
Аннотация
Interpretability of results remains challenging in most health industries since patients may suffer life-threatening consequences from an inaccurate diagnosis. Artificial intelligence (AI) integration has arisen as a prominent technology in the healthcare sector, transforming the field by advancing early diagnostics, surgeries, and ethical concerns. The present review analyzes the multidimensional impact of AI on the health sector through enhancements in medical accuracy and diagnosis outcomes. Implementing AI techniques and machine learning algorithms in predictive analytics enables disease identification at a nascent stage, boosting decision-making accuracy. Advancements in genomics have demanded the employment of AI in decoding genetic information supporting personalized and targeted treatments. The review comprehensively examines the application of AI-based diagnostics addressing the impact on heart-associated diseases, cancer pathogenesis, and other general disease prediction. Different machine learning algorithms aid in identifying tumor behavior, risk factors, and tailored therapy in cancer treatment. In the context of cardiovascular disorders, AI-driven methodologies aid in assessing patient data, evaluating risk factors, and forecasting probable complications in preventative care. AI-based surgeries employing the da Vinci Surgical System highlight the use of AI in increasing the prediction of surgical success rate. Robotic automation in orthopedics advances spine and joint replacement surgeries, offering real-time guidance and enhancing patient recovery outcomes. Broader improvements in AI integration in healthcare have been discussed, focusing on refining algorithms for improved application.