article · Health Science Reports
This study acknowledges the significant influence of artificial intelligence on laboratory medicine within low- and middle-income countries. It identifies several key challenges, including inadequate data availability, deficiencies in digital infrastructure, and ethical considerations. For successful implementation of AI, the research highlights the necessity of substantial investments in digital infrastructure, the establishment of robust data-sharing networks, and the development of clear regulatory frameworks. The study concludes that collaborative efforts are essential among various stakeholders, such as international organisations, governments, and non-governmental entities, to overcome these obstacles. A comprehensive and coordinated approach is crucial to fully realise AI's transformative potential and advance healthcare in these regions.
Understanding the challenges and recommendations for AI in laboratory medicine in low- and middle-income countries is vital. It highlights the systemic changes needed to harness AI's potential, ensuring that technological advancements contribute effectively to improving healthcare diagnostics and services in resource-constrained settings.
The abstract focuses on the foundational requirements for integrating AI into laboratory medicine in low- and middle-income countries, rather than specific AI applications. It suggests that investments in digital infrastructure, data-sharing platforms, and regulatory frameworks are necessary preconditions. This work could inform policy and investment strategies for organisations aiming to facilitate AI adoption in healthcare, but it does not indicate a direct commercialisation pathway for a specific product or service.
AI-generated from the published abstract. Always read the original work before citing.
While acknowledging the profound impact of AI on laboratory medicine in LMICs, the study recognizes challenges such as inadequate data availability, digital infrastructure deficiencies, and ethical considerations. Successful implementation necessitates substantial investments in digital infrastructure, the establishment of data-sharing networks, and the formulation of regulatory frameworks. The study concludes that collaborative efforts among stakeholders, including international organizations, governments, and nongovernmental entities, are crucial for overcoming obstacles and responsibly integrating AI into laboratory medicine in LMICs. A comprehensive, coordinated approach is essential for realizing AI's transformative potential and advancing health care in LMICs.
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DOI: 10.1002/hsr2.1794
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