{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jones GD"],"funding":["National Institute for Health Research (NIHR)","Wellcome Trust"],"pagination":["e185-e193"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7618270"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["5(4)"],"pubmed_abstract":["<h4>Background</h4>Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa.<h4>Methods</h4>In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset an"],"journal":["The Lancet. Digital health"],"pubmed_title":["Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study."],"pmcid":["PMC7618270"],"funding_grant_id":["NIHR200134","083744"],"pubmed_authors":["Kakooza A","McDaid D","Mtai Mwanga D","Agbokey F","Grassi S","Denison T","Chabi M","Collinson M","Bauni E","Doku V","Abban H","Kariuki SM","Bottomley C","Sander J","Sen A","O Mageto J","Muli D","Tollman S","Odhiambo R","Kahn K","Connor M","Sylvester I","Junior DNYA","Akpalu B","Mathew A","Walker R","Newton CR","Akpalu A","Murunga Wekesah F","Sander JW","Ngugi AK","Otieno P","Aissaoui L","Atieno M","Khalayi C","Wagner R","Darkwa E","Ngugi A","Peterson S","Chowdhary N","Vallentin S","Kamuyu G","Thoya Y","Adjei P","Kwasa T","Egesa I","Kariuki S","Mung'ala Odera V","Mushi V","Masanja H","Cross H","Cross JH","Twine R","Gomez-Olive FX","Mahone S","Kleinschmidt I","Sottie C","Jones GD","Pariyo G","Bitta M","Mmbando B","Matuja W","Odermatt P","Waruingi S","Mwesige AK","Asiki G","Dua T","Godi T","Iddi S","Manolova G","EPInA Study Group","Kimambo H","Asiamah S","Chengo E","Bhwana D","Ae-Ngibise K","Owusu-Agyei S"],"additional_accession":[]},"is_claimable":false,"name":"Development and validation of a diagnostic aid for convulsive epilepsy in sub-Saharan Africa: a retrospective case-control study.","description":"<h4>Background</h4>Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa.<h4>Methods</h4>In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset an","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Apr","modification":"2026-06-04T15:03:28.093Z","creation":"2026-06-02T03:08:30.467Z"},"accession":"S-EPMC7618270","cross_references":{"pubmed":["36963908"],"doi":["10.1016/S2589-7500(22)00255-2"]}}