International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 6
November-December 2024
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Enhancing Long-Term Care with Explainable AI: Improving Patient Outcomes, Caregiver Support, and Ethical Transparency
Author(s) | Bhanu Prakash Manjappasetty Masagali |
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Country | United States |
Abstract | This paper explores the potential impact of Explainable Artificial Intelligence (XAI) on long-term care (LTC), highlighting the value of transparent and interpretable AI in supporting clinical decision-making, enhancing patient trust, and improving the quality of care. With an aging global population, LTC facilities are increasingly adopting AI tools to manage patient health and operational efficiency. XAI can play a critical role by ensuring that predictions and recommendations are understandable and actionable for caregivers and clinicians, fostering trust, accountability, and ethical use of AI in patient care. |
Keywords | Explainable AI (XAI), Long-Term Care (LTC), Healthcare Decision-Making, Predictive Analytics in Healthcare, Patient Outcomes, Transparency in AI, AI in Elderly Care, Ethics in AI, Trust in AI, AI-Assisted Diagnosis, Caregiver Support, Patient-Centric AI Models, AI Interpretability, Human-AI Collaboration, Healthcare Personalization |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 6, Issue 6, November-December 2024 |
Published On | 2024-11-19 |
Cite This | Enhancing Long-Term Care with Explainable AI: Improving Patient Outcomes, Caregiver Support, and Ethical Transparency - Bhanu Prakash Manjappasetty Masagali - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.31020 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i06.31020 |
Short DOI | https://doi.org/ |
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