Augmented AI in Health Diagnostics: Enhancing Medical Decision Making through Artificial Intelligence

Dhivya Sudeep

Abstract: The integration of Artificial Intelligence (AI) in Health Diagnosis presents a transformative approach in improving Health outcomes. According to a Harvard Medical school study, the estimated market for AI is expected to be around $21.74 Billion by 2032 compared to $1.07 Billion in 2022[1]. The world Economic Forum also predicted that AI could help with improved health outcomes with its ability to use data from diverse and concealed sources that have been existed across healthcare.[6] This paper explores various AI diagnostic models that can improve diagnosis and inspect real-life use cases of AI for medical diagnosis. By integrating vast amounts of medical data, including electronic health records, imaging records, and genomic information, Augmented AI facilitates a more comprehensive understanding of patient conditions. This review paper further highlights the promising future of Augmented AI as a vital tool in the evolution of medical diagnostics, aiming to enhance both clinician performance and patient outcomes.

Keywords: Artificial Intelligence, Augmented AI, Natural Language Processing (NLP), Large language Models (LLM), machine learning, medical diagnosis, lung cancer detection, diabetic retinopathy, breast cancer detection

How to Cite?: Dhivya Sudeep, "Augmented AI in Health Diagnostics: Enhancing Medical Decision Making through Artificial Intelligence", Volume 13 Issue 10, October 2024, International Journal of Science and Research (IJSR), Pages: 1645-1648, https://www.ijsr.net/getabstract.php?paperid=SR241022231140, DOI: https://dx.doi.org/10.21275/SR241022231140