Authors : Sanku Nithin Sai; Sai Baba CH; Yarlagadda Hitesh Sai; Thamma Sasank Reddy

Volume/Issue : Volume 9 - 2024, Issue 7 - July

Google Scholar : https://tinyurl.com/4n76wn2c

DOI : https://doi.org/10.38124/ijisrt/24jul1574

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The field of artificial intelligence (AI) is rapidly evolving and has the potential to drastically alter the healthcare industry. This abstract delves into the transformative role of AI in the healthcare sector, highlighting its applications, benefits, challenges, and ethical considerations. Better patient outcomes, more individualized care, and better diagnosis have all come from the use of AI in healthcare. Machine learning algorithms can analyze vast amounts of medical data, aiding in early disease detection and accurate diagnosis. AI-powered predictive models enable healthcare professionals to anticipate disease trends and allocate resources effectively, thus bolstering public health efforts. Moreover, AI assists in tailoring treatment plans to individual patients by analyzing genetic and clinical data, leading to more effective interventions and reduced adverse effects. Ethical considerations play a crucial part in the implementation of AI in healthcare. Striking a balance between innovative advancements and preserving patient autonomy, privacy, and informed consent requires a comprehensive framework. Additionally, the potential displacement of certain healthcare roles by AI systems prompts discussions about workforce reskilling and redefining human-AI collaboration in medical settings. In conclusion, AI holds substantial promise in revolutionizing healthcare by expediting diagnostics, enhancing treatment strategies, and advancing public health efforts. However, successful integration requires addressing technical, ethical, and privacy-related challenges.

Keywords : Artificial Intelligence, Enhanced Diagnosis, Machine Learning Algorithms, Patient Autonomy, Workforce Reskilling, Revolutionizing Healthcare.

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