Local transplantation, adaptation, and creation of AI models for public health policy.

This paper presents the Transplantation, Adaptation and Creation (TAC) framework, a method for assessing the localization of different elements of an AI system. This framework is applied in the public health context, notably to different types of models that were used during the COVID-19 pandemic. The framework aims to guide AI for public health developers and public health officials in conceptualizing model localization.

A Medical Ethics Framework for Conversational Artificial Intelligence.

The launch of OpenAI's GPT-3 model in June 2020 began a new era for conversational chatbots. While there are chatbots that do not use artificial intelligence (AI), conversational chatbots integrate AI language models that allow for back-and-forth conversation between an AI system and a human user. GPT-3, since upgraded to GPT-4, harnesses a natural language processing technique called sentence embedding and allows for conversations with users that are more nuanced and realistic than before.

Tropicalisation of epidemiological models in Africa: A mixed and hybrid approach to better predict COVID-19 indicators.

Context: Since the outbreak of the SARS-COV2 epidemic turned into a COVID-19 pandemic, international bodies such as the WHO as well as governments have announced projections for morbidity and mortality indicators related to COVID-19. Most of them indicated that the health situation would be worrying. Although using artificial intelligence with mathematical algorithms and/or neural networks, the results of the SIR models were poorly performing and not very accurate in relation to the observed reality in the African states in general and in Senegal in particular.