Explainable AI in Healthcare: Enhancing Decision-Making for Clinical Applications
Year: 2024
Type: article
Abstract: The application of AI in healthcare encompasses and invokes a gamut of fields and meanings, including the following: diagnostics, to provide earlier detection of disease and predictive analytics; and personalized medicine, or tailor-made therapies according to genetic and health information. AI is analyzed deeply in relation to its role in medical imaging, treatment planning, operational efficiency, disease management, and drug discovery, highlighting its potential to improve healthcare outcomes and optimize resources. Challenges it raises include bias, data privacy, and transparency; suggested solutions outline the possibility of responsible deployment of AI systems. In conclusion, the report outlines the future trends along with AI, establishing AI as an enhancer of precision medicine and preparedness for global health. This work underlines a call to explainable, accountable AI that will unleash its maximum potential in healthcare innovation.
Author: Gopalakrishnan Arjunan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949343425
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