Authors: Samaira Lodh
Abstract: Artificial Intelligence (AI) is revolutionizing healthcare diagnostics by providing unprecedented capabilities in data analysis, pattern recognition, and predictive modeling. AI-powered tools have demonstrated potential in increasing diagnostic accuracy, reducing diagnostic errors, optimizing treatment pathways, and ultimately improving patient outcomes. The integration of AI with healthcare diagnostics stands at the forefront of digital transformation, leveraging advancements in machine learning, deep learning, and natural language processing. These technologies enable precise identification of diseases from various forms of medical data, including imaging, genomics, and patient records. Despite remarkable progress, the field faces challenges such as data privacy concerns, ethical dilemmas, integration with existing healthcare workflows, and the need for transparency and explainability in AI-driven decisions. Emerging trends like explainable AI, federated learning, and the use of AI for point-of-care diagnostics are shaping the future of healthcare diagnostics. This article explores these trends, evaluates their potential impact, and discusses the implications for practitioners, patients, and policymakers. The ultimate aim is to provide an in-depth understanding of how AI is redefining healthcare diagnostics, the directions in which the field is evolving, and the unresolved questions that must be addressed to leverage the full potential of AI while safeguarding ethical and clinical standards.
DOI: https://doi.org/10.5281/zenodo.16979367
