Magda César Raposo
A5071796929- COVID-19 diagnosis using AI
- Machine Learning in Healthcare
- Health Literacy and Information Accessibility
- Medication Adherence and Compliance
- Mobile Health and mHealth Applications
- Telemedicine and Telehealth Implementation
- Explainable Artificial Intelligence (XAI)
- COVID-19 and healthcare impacts
- Artificial Intelligence in Healthcare
- COVID-19 Clinical Research Studies
- Blood Pressure and Hypertension Studies
Federal University of São João del-Rei
2021-2023
Although a great number of teleconsultation services have been developed during the COVID-19 pandemic, studies assessing usability and health care provider satisfaction are still incipient.This study aimed to describe development, implementation, expansion synchronous service targeting patients with symptoms in Brazil, as well assess its professionals' satisfaction.This mixed methods was 5 phases: (1) identification components, technical functional requirements, system architecture; (2) user...
Abstract The majority of early prediction scores and methods to predict COVID-19 mortality are bound by methodological flaws technological limitations (e.g., the use a single model). Our aim is provide thorough comparative study that tackles those issues, considering multiple techniques build models, including modern machine learning (neural) algorithms traditional statistical techniques, as well meta-learning (ensemble) approaches. This used dataset from multicenter cohort 10,897 adult...
Abstract Background Warfarin remains the most affordable oral anticoagulant in many countries. However, it may have serious side effects, and success of therapy depends on patient’s understanding medication their adherence to treatment. The use short messages services (SMS) is a strategy that can be used educate patients, but there are no studies evaluating this intervention patients taking warfarin. Therefore, we aimed develop, implement, assess feasibility an using SMS primary care...
Abstract Objective To provide a thorough comparative study among state-of-the-art machine learning methods and statistical for determining in-hospital mortality in COVID-19 patients using data upon hospital admission; to the reliability of predictions most effective by correlating probability outcome accuracy methods; investigate how explainable are produced methods. Materials Methods De-identified were obtained from positive 36 participating hospitals, March 1 September 30, 2020....
Abstract The majority prognostic scores proposed for early assessment of coronavirus disease 19 (COVID-19) patients are bounded by methodological flaws. Our group recently developed a new risk score - ABC 2 SPH using traditional statistical methods (least absolute shrinkage and selection operator logistic regression LASSO). In this article, we provide thorough comparative study between modern machine learning (ML) state-of-the-art methods, represented SPH, in the task predicting in-hospital...
Abstract Background: Warfarin remains the most affordable oral anticoagulant in many countries. However, it may have serious side effects, and success of therapy depends on patient's understanding medication their adherence to treatment. The use short messages services (SMS) is a strategy that can be used educate patients, but there are no studies evaluating this intervention patients taking warfarin. Therefore, our aim was report implementation text-messaging primary care warfarin...