A new 50-conversation benchmark shows commercial ASR and diarization models degrade notably on African-accented conversational English.
What We Know So Far: Artificial Intelligence in African Healthcare
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abstract
Healthcare in Africa is a complex issue influenced by many factors including poverty, lack of infrastructure, and inadequate funding. However, Artificial intelligence (AI) applied to healthcare, has the potential to transform healthcare in Africa by improving the accuracy and efficiency of diagnosis, enabling earlier detection of diseases, and supporting the delivery of personalized medicine. This paper reviews the current state of how AI Algorithms can be used to improve diagnostics, treatment, and disease monitoring, as well as how AI can be used to improve access to healthcare in Africa as a low-resource setting and discusses some of the critical challenges and opportunities for its adoption. As such, there is a need for a well-coordinated effort by the governments, private sector, healthcare providers, and international organizations to create sustainable AI solutions that meet the unique needs of the African healthcare system.
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cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Afrispeech-Dialog: A Benchmark Dataset for Spontaneous English Conversations in Healthcare and Beyond
A new 50-conversation benchmark shows commercial ASR and diarization models degrade notably on African-accented conversational English.