Lívia Oliveira-Ciabati

Feasibility study of an AI-powered mobile app to support cutaneous leishmaniasis diagnosis in the Brazilian Amazon

Karina Lumy Okita, Thamires Bastos Pinheiro, Lívia Oliveira-Ciabati, Breno dos Santos Alves et autres

br (code pays fourni par la source)

Mapping the potential and limitations of using generative AI technologies to address socio-economic challenges in LMICs

Rachel Adams, Fola Adeleke, Leah Junck, Ayantola Alayande et autres

ca, Ouganda, us, Ghana, cn, lb, Nigéria, gb, Tanzanie, Rwanda, br, ch, Sénégal, hk, pk, bd, Malawi, Afrique du Sud, jp, Kenya, Mali, in (code pays fourni par la source)

Mapping the Potentials and Limitations of Using Generative AI Technologies to Address Socio-Economic Challenges in LMICs

Rachel Adams, Fola Adeleke, Leah Junck, Ayantola Alayande et autres

ca, us, Ouganda, au, Afrique du Sud, Nigéria, in, cn, bd, Sénégal, lb, Tanzanie, gb, np, Kenya, Mali, br, hk, pk, Rwanda, id, Malawi, ch (code pays fourni par la source)

Application of Artificial Intelligence in the Early Diagnosis of Potentially Malignant Skin Lesions: A Cross-Sectional Study in a Population Assisted by the Public Health System in Brazil

Matheus Tavella da Silva, Marília Jesus Batista, Karina Lumy Okita, Lívia Oliveira-Ciabati et autres

br (code pays fourni par la source)

Artificial Intelligence for Automated Thoracic Aorta Diameter Measurement Using Different Computed Tomography Protocols

Maria Fernanda Cassino Portugal, Lucas Lembrança Pinheiro, Henrique Min Ho Lee, Henrique Cursino Vieira et autres

br (code pays fourni par la source)

Early warning systems for identifying severe maternal outcomes: findings from the WHO global maternal sepsis study

Yamikani Chimwaza, Alexandra Hunt, Lívia Oliveira-Ciabati, Laura Bonnett et autres

gb, Malawi, br, ar, ch (code pays fourni par la source)

Scientific production in sexual and reproductive health and rights research according to gender and affiliation: An analysis of publications from 1972 to 2021

Lívia Oliveira-Ciabati, Anna Thorson, Vanessa Brizuela

br, ch (code pays fourni par la source)

Unveiling the strong positive relationship: Maternal characteristics and neonatal outcomes in the Better Outcomes in Labour Difficulty (BOLD) study – a secondary analysis validating neonatal near miss classification

Vicky Nogueira Pileggi, Olufemi T. Oladapo, João Paulo Souza, Hayala Cristina Cavenague de Souza et autres

br, ch, Nigéria (code pays fourni par la source)

Early Warning Systems for Identifying Severe Maternal Outcomes in the Who Global Maternal Sepsis Study

Yamikani Chimwaza, Alexandra Hunt, Lívia Oliveira-Ciabati, Laura Bonnett et autres

Artificial intelligence for automated thoracic aorta diameter measurement using different computed tomography protocols

Maria Fernanda Cassino Portugal, Lucas Lembrança Pinheiro, Henrique Min Ho Lee, Henrique Cursino Vieira et autres

br (code pays fourni par la source)

Artificial intelligence for automated thoracic aorta diameter measurement using different computed tomography protocols

Maria Fernanda Cassino Portugal, Lucas Lembrança Pinheiro, Henrique Min Ho Lee, Henrique Cursino Vieira et autres

br (code pays fourni par la source)

[Factors associated with serious maternal morbidity in Ribeirão Preto, São Paulo State, Brazil: a cross-sectional cohort study].

Magna Santos Andrade, Lívia Pimenta Bonifácio, Jazmin Andrea Cifuentes Sanchez, Lívia Oliveira-Ciabati et autres

br (code pays fourni par la source)