Browsing by Author "Hamusonde, Kalongo"

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    Performance of Machine Learning Classifiers in Classifying Stunting among Under-Five Children in Zambia.
    (2022-Jul-20) Chilyabanyama, Obvious N.; Chilengi, Roma; Simuyandi, Michelo; Chisenga, Caroline C.; Chirwa, Masuzyo; Hamusonde, Kalongo; Saroj, Rakesh K.; Iqbal, Najeeha T.; Ngaruye, Innocent ; Bosomprah, Samuel
    Stunting is a global public health issue. We sought to train and evaluate machine learning (ML) classification algorithms on the Zambia Demographic Health Survey (ZDHS) dataset to predict stunting among children under the age of five in Zambia. We applied Logistic regression (LR), Random Forest (RF), SV classification (SVC), XG Boost (XgB) and Naïve Bayes (NB) algorithms to predict the probability of stunting among children under five years of age, on the 2018 ZDHS dataset. We calibrated predicted probabilities and plotted the calibration curves to compare model performance. We computed accuracy, recall, precision and F1 for each machine learning algorithm. About 2327 (34.2%) children were stunted. Thirteen of fifty-eight features were selected for inclusion in the model using random forest. Calibrating the predicted probabilities improved the performance of machine learning algorithms when evaluated using calibration curves. RF was the most accurate algorithm, with an accuracy score of 79% in the testing and 61.6% in the training data while Naïve Bayesian was the worst performing algorithm for predicting stunting among children under five in Zambia using the 2018 ZDHS dataset. ML models aids quick diagnosis of stunting and the timely development of interventions aimed at preventing stunting.
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    Screening test accuracy to improve detection of precancerous lesions of the cervix in women living with HIV: a study protocol.
    (2020-Dec-18) Taghavi, Katayoun; Moono, Misinzo; Mwanahamuntu, Mulindi; Basu, Partha; Limacher, Andreas; Tembo, Taniya; Kapesa, Herbert; Hamusonde, Kalongo; Asangbeh, Serra; Sznitman, Raphael; Low, Nicola; Manasyan, Albert; Bohlius, Julia
    INTRODUCTION: The simplest and cheapest method for cervical cancer screening is visual inspection after application of acetic acid (VIA). However, this method has limitations for correctly identifying precancerous cervical lesions (sensitivity) and women free from these lesions (specificity). We will assess alternative screening methods that could improve sensitivity and specificity in women living with humanimmunodeficiency virus (WLHIV) in Southern Africa. METHODS AND ANALYSIS: We will conduct a paired, prospective, screening test accuracy study among consecutive, eligible women aged 18-65 years receiving treatment for HIV/AIDS at Kanyama Hospital, Lusaka, Zambia. We will assess a portable magnification device (Gynocular, Gynius Plus AB, Sweden) based on the Swede score assessment of the cervix, test for high-risk subtypes of human papillomavirus (HR-HPV, GeneXpert, Cepheid, USA) and VIA. All study participants will receive all three tests and the reference standard at baseline and at six-month follow-up. The reference standard is histological assessment of two to four biopsies of the transformation zone. The primary histological endpoint is cervical intraepithelial neoplasia grade two and above (CIN2+). Women who are VIA-positive or have histologically confirmed CIN2+ lesions will be treated as per national guidelines. We plan to enrol 450 women. Primary outcome measures for test accuracy include sensitivity and specificity of each stand-alone test. In the secondary analyses, we will evaluate the combination of tests. Pre-planned additional studies include use of cervigrams to test an automated visual assessment tool using image pattern recognition, cost-analysis and associations with trichomoniasis. ETHICS AND DISSEMINATION: Ethical approval was obtained from the University of Zambia Biomedical Research Ethics Committee, Zambian National Health Regulatory Authority, Zambia Medicines Regulatory Authority, Swissethics and the International Agency for Research on Cancer Ethics Committee. Results of the study will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT03931083; Pre-results.