研究论文
Mapping the potential and limitations of using generative AI technologies to address socio-economic challenges in LMICs
Rachel Margaret Adams, Fola Adeleke, Leah Junck, Ayantola Alayande, Aarushi Gupta, Urvashi Aneja, Samuel T. Segun, Rosalind M. Parkes-Ratanshi 等 75 位
Queen's University Belfast Infectious Diseases Institute Gates Foundation Jiangsu Academy of Agricultural Sciences
来源Nature Computational Science
年份2026
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学术脉络
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社会科学Ethics and Social Impacts of AI
Artificial Intelligence in Healthcare and Education · ICT in Developing Communities
参考文献 28
Is agricultural adaptation to global change in lower-income countries on track to meet the future food production challenge?
被引 124Philip K. Thornton, Patti Kristjanson, Wiebke Förch · Global Environmental Change · 2018
Maternal Mortality and Maternal Health Care in Nigeria: Implications for Socio-Economic Development
被引 143Olawale Yinusa Olonade, Tomike Ibironke Olawande, Oluwatobi Joseph Alabi · Open Access Macedonian Journal of Medical Sciences · 2019
Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
被引 298Antoine L. Harfouche, Antoine L. Harfouche, Daniel Jacobson · Trends in biotechnology · 2019
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引用本文 1
The Infrastructure Paradox of AI Development in LMICs
被引 0Samuel T. Segun, Patrick Onodje, Ayantola Alayande · Research Square · 2026
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