Developing a Responsible AI Framework for Healthcare in Low Resource Countries: A Case Study in Nepal and Ghana
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915448784683008 |
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| author | Neupane, Hari Krishna Mishra, Bhupesh Kumar |
| author_facet | Neupane, Hari Krishna Mishra, Bhupesh Kumar |
| contents | The integration of Artificial Intelligence (AI) into healthcare systems in low-resource settings, such as Nepal and Ghana, presents transformative opportunities to improve personalized patient care, optimize resources, and address medical professional shortages. This paper presents a survey-based evaluation and insights from Nepal and Ghana, highlighting major obstacles such as data privacy, reliability, and trust issues. Quantitative and qualitative field studies reveal critical metrics, including 85% of respondents identifying ethical oversight as a key concern, and 72% emphasizing the need for localized governance structures. Building on these findings, we propose a draft Responsible AI (RAI) Framework tailored to resourceconstrained environments in these countries. Key elements of the framework include ethical guidelines, regulatory compliance mechanisms, and contextual validation approaches to mitigate bias and ensure equitable healthcare outcomes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_12389 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Developing a Responsible AI Framework for Healthcare in Low Resource Countries: A Case Study in Nepal and Ghana Neupane, Hari Krishna Mishra, Bhupesh Kumar Computers and Society The integration of Artificial Intelligence (AI) into healthcare systems in low-resource settings, such as Nepal and Ghana, presents transformative opportunities to improve personalized patient care, optimize resources, and address medical professional shortages. This paper presents a survey-based evaluation and insights from Nepal and Ghana, highlighting major obstacles such as data privacy, reliability, and trust issues. Quantitative and qualitative field studies reveal critical metrics, including 85% of respondents identifying ethical oversight as a key concern, and 72% emphasizing the need for localized governance structures. Building on these findings, we propose a draft Responsible AI (RAI) Framework tailored to resourceconstrained environments in these countries. Key elements of the framework include ethical guidelines, regulatory compliance mechanisms, and contextual validation approaches to mitigate bias and ensure equitable healthcare outcomes. |
| title | Developing a Responsible AI Framework for Healthcare in Low Resource Countries: A Case Study in Nepal and Ghana |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2508.12389 |