Bridging AI, NLP, and Digital Health: A Bi-Directional Learning Experience at Emory University

Digital health, natural language processing, and artificial intelligence collectively possess considerable promise, with the potential to transform healthcare particularly within resource-limited settings. This manuscript discusses a research fellowship at the Department of Biomedical Informatics at Emory University, focusing on the outcomes of applying AI and NLP to address healthcare challenges in low- and middle-income countries (LMICs) and the bi-directional learning between academia and real-world field application. The fellowship explored multilingual generative language models, gender bias in NLP, and conversational AI, demonstrating its application through the enhanced development of AvivaAI, a mobile conversational chatbot for cervical cancer awareness in Nigeria.