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The Performance Of Machine Learning Algorithms In Predicting Under-Five Anaemia In Tanzania, Henry Ofori Duah, Derrick Nyantakyi Owusu, Godwin G. Duah, Paul Shidende

College of Nursing Faculty Research and Publications

Aim

Anaemia in children under five remains a major public health concern, contributing significantly to global child morbidity and mortality. With the rise of machine learning (ML), novel opportunities exist to model and predict anaemia more effectively. This study aimed to evaluate and compare the performance of five ML algorithms in predicting anaemia among under-five children in Tanzania.

Methods

We conducted a secondary data analysis using the 2017 Tanzania Malaria Indicator Survey (TMICS). The dataset (n = 5906) was randomly split into training (70%) and test (30%) sets. Five ML algorithms, Linear Discriminant Analysis (LDA), Logistic Regression, Random Forest (RF), …

Ai For Prognosis Among People Living With Hiv: Protocol For A Systematic Review And Meta-Analysis, Degninou Yehadji, Markus Hofmann, Petros Isaakidis, Smaila Alidou, Olushina Ayo Junior Ale, Kofivi Mawouko Yena, Kodjo Guidigan, Geraldine Gray, Nadjime Pindra, Gayo Diallo

Research Outputs: 2025-Present

Background: Advanced HIV disease remains a major global health concern, with nearly 40.8 million people living with HIV as of 2024. Antiretroviral therapy has improved outcomes, but its success depends on timely intervention, adherence, and retention in care. AI, including machine learning and deep learning, offers promising tools for prognostic modeling that could support clinical decision-making and personalized treatment. Existing syntheses, however, have been largely narrative and have not systematically evaluated the performance, risk of bias, reporting quality, or clinical readiness of AI-based prognostic models, leaving a critical gap in understanding their validity and applicability. Objective: This study aims to …

A Comparison Of F/Taf And F/Tdf As Hiv Pre-Exposure Prophylaxis In A Predominantly Cisgender Women Population In East And South Africa: A Randomised, Factorial, Non-Inferiority Trial, Sheena Mccormack, David Dunn, Sylvia Kusemererwa, Patricia Munseri, Nishanta Singh, Wiston William, Gertrude Mutonyi, Henry Bern, Lauriane Goldwirt, Cherry Kingsley, Arne Kkroidl, Christian Holm Hansen, Song Ding, Rachel Kawuma, Mary Amondi, Ubaldo Bahemuka, Deus Buma, Daniel Clutterbuck, Zakir Gaffoor, Angus Jennings, Agricola Joachim, Ayoub Kakande, Berna Kalanzi, Abisai Kisinda, Mabela Matsoso, Thomas Miller, Neetha Mmedsci Morar, Jacqueline Musau, Jane Nabbuto, Ayanda Nzuza, Doreen Pamba, Simona Salomone, Thandiwe Sithole, Edith Tarimo, Kubashni Woeber, Kundai Chinyenze, Glenda Gray, Eligius Lyamuya, Muhammad Bakari, Said Aboud, Lucas Maganga, Gustavo Doncel, Janet Seeley, Jonathan Weber, Pontiano Kaleebu, Julie Fox, Eugene Ruzagira, On Behalf Of The Prepvacc Study Group

CONRAD Publications

Background:

F/TAF was shown to be non-inferior to F/TDF as pre-exposure prophylaxis (PrEP) in men, but approval was not extended to cisgender women. We report the results of PrEPVacc, in which a predominantly female population was randomly allocated to receive daily oral F/TDF or F/TAF for ∼6 months within a HIV-1 prophylactic vaccine trial.

Setting:

Five study sites in three African countries (Uganda, Tanzania, South Africa).

Methods:

The two regimens were compared by the averted infections ratio (AIR) - the proportion of infections averted by F/TAF relative to F/TDF. The counterfactual HIV incidence, an essential component of this metric, was …

Cross-Domain Antimicrobial Resistance In Poultry Farming: A One Health Assessment Of Antimicrobial Use And Multidrug Resistance In Kiambu County, Kenya, Ann Kangai Munene, Peter Muiruri Mwangi, Lilly Caroline Bebora, Christine Minoo Mbindyo, John Muthini Maingi

All Peer-Reviewed Publications

Background and Aim: Antimicrobial resistance (AMR) has emerged as a major One Health threat driven by inappropriate antimicrobial use (AMU) in humans, animals, and the environment. Poultry production is recognized as a key reservoir of antimicrobial-resistant bacteria, yet few studies in Kenya examine AMU and AMR across interconnected human–animal–environment domains. This study assessed AMU patterns among poultry farmers in Kiambu County and characterized phenotypic resistance in Escherichia coli and Enterococcus spp. isolated from humans, chickens, and chicken environments. Materials and Methods: A cross-sectional study was conducted from May to September 2024, involving 102 poultry farms. Farm demographics and AMU data …