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Maha R Farhat

Dados Biográficos

ID9068680
NOMEMaha R Farhat
PRENOMESMaha R
SOBRENOMEFarhat
ASSINATURAFARHAT M R
AFILIAÇÕESHarvard Medical School
VERIFICADONão
TOTAL DE OBRAS2
TOTAL DE CITAÇÕES0
OBRAS COMO AUTOR2
OBRAS COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2023
ANO MAIS RECENTE DE PUBLICAÇÃO2024
ÍNDICE H0
  • Estimation of country-specific tuberculosis resistance antibiograms using pathogen genomics and machine learning

    Open Access•Avika Dixit, Luca Freschi et al.•ARTICLE•BMJ Global Health•2024

    BACKGROUND: ) whole-genome sequencing (WGS) data, to generate expanded country-level resistance prevalence estimates (antibiograms) using in silico resistance prediction. METHODS: WGS data. We used a validated random forest model to predict phenotypic resistance to 12 drugs and bias-corrected for model performance, outbreak sampling and rifampicin resistance oversampling. Validation leveraged a national DR survey conducted in South Africa. RESULT…

  • Rethinking global digital health and AI-for-health innovation challenges

    Open Access•Andrew Farlow, Alexander Hoffmann et al.•ARTICLE•PLOS Global Public Health•2023

    Digital health technologies can help tackle challenges in global public health. Digital and AI-for-Health Challenges, controlled events whose goal is to generate solutions to a given problem in a defined period of time, are one way of catalysing innovation. This article proposes an expanded investment framework for Global Health AI and digitalhealth Innovation that goes beyond traditional factors such as return on investment. Instead, we propose …

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  • Rethinking global digital health and AI-for-health innovation challenges

    Open Access•Andrew Farlow, Alexander Hoffmann et al.•ARTICLE•PLOS Global Public Health•2023

    Digital health technologies can help tackle challenges in global public health. Digital and AI-for-Health Challenges, controlled events whose goal is to generate solutions to a given problem in a defined period of time, are one way of catalysing innovation. This article proposes an expanded investment framework for Global Health AI and digitalhealth Innovation that goes beyond traditional factors such as return on investment. Instead, we propose …

  • Estimation of country-specific tuberculosis resistance antibiograms using pathogen genomics and machine learning

    Open Access•Avika Dixit, Luca Freschi et al.•ARTICLE•BMJ Global Health•2024

    BACKGROUND: ) whole-genome sequencing (WGS) data, to generate expanded country-level resistance prevalence estimates (antibiograms) using in silico resistance prediction. METHODS: WGS data. We used a validated random forest model to predict phenotypic resistance to 12 drugs and bias-corrected for model performance, outbreak sampling and rifampicin resistance oversampling. Validation leveraged a national DR survey conducted in South Africa. RESULT…

Medicine (2 obras) · Antibiotic resistance (1 obra) · Antibiotic Use and Resistance (1 obra) · Antibiotics (1 obra) · Artificial Intelligence in Healthcare and Education (1 obra) · Biology (1 obra) · Biomedical and Engineering Education (1 obra) · Business (1 obra) · Computer Science (1 obra) · Digital health (1 obra)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae