Abstract
<p>Machine learning (ML) and Artificial intelligence (AI) have demonstrated substantial promise for enhancing healthcare diagnostics and therapy. This study compares the benefits, drawbacks, and uses of these tools to examine their potential in healthcare. ML systems can find trends, increase diagnosis precision, and support professional judgment. Their efficacy may be constrained, though, by bad data quality, a lack of interpretability, and execution issues. On the other hand, AI can support clinical judgment, enhance patient results, and boost healthcare productivity. However, difficulties in implementing them can arise due to restricted generalizability, data protection issues, and legal conformance. To ensure the effective application and acceptance of these technologies in healthcare, it is essential to understand these benefits and constraints. Healthcare providers of the future will be able to make wiser choices regarding patient assessment and therapy options using AL and ML, resulting in an overall enhancement of healthcare services.</p>
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
