Shubhangi Mhaske, Karthikeyan Ramalingam, Preeti Nair, Shubham Patel, Arathi Menon P, Nida Malik, Sumedh Mhaske
Automated Analysis of Nuclear Parameters in Oral Exfoliative Cytology Using Machine Learning
Cureus
longitudinal study examined predictors dropout assessed elementary school student demographic data achievement attendance ratings behavior behavior assessment system children used predict dropout completion two models varied student sex race predicted dropout rates ranging 75 88 model included behavioral symptoms index school problems composite iowa tests basic skills battery teacher ratings student work habits best predicted female african american dropouts model b comprised adaptive skills composite externalizing composite school problems composite referral student support team meeting sex accurate predicting caucasian dropouts models demonstrated hit rates predicting male dropouts recommendations early warning indicators linking predictors interventions discussed