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Full-Text Articles in Medicine and Health Sciences
Sociodemographic Determinants Of Oral Anticoagulant Prescription In Patients With Atrial Fibrillations: Findings From The Pinnacle Registry Using Machine Learning, Zahra Azizi, Andrew T. Ward, Donghyun J. Lee, Sanchit S. Gad, Kanchan Bhasin, Robert J. Beetel, Tiago Ferreira, Sushant Shankar, John S. Rumsfeld, Salim S. Virani
Sociodemographic Determinants Of Oral Anticoagulant Prescription In Patients With Atrial Fibrillations: Findings From The Pinnacle Registry Using Machine Learning, Zahra Azizi, Andrew T. Ward, Donghyun J. Lee, Sanchit S. Gad, Kanchan Bhasin, Robert J. Beetel, Tiago Ferreira, Sushant Shankar, John S. Rumsfeld, Salim S. Virani
Office of the Provost
Background: Current risk scores that are solely based on clinical factors have shown modest predictive ability for understanding of factors associated with gaps in real-world prescription of oral anticoagulation (OAC) in patients with atrial fibrillation (AF).
Objective: In this study, we sought to identify the role of social and geographic determinants, beyond clinical factors associated with variation in OAC prescriptions using a large national registry of ambulatory patients with AF.
Methods: Between January 2017 and June 2018, we identified patients with AF from the American College of Cardiology PINNACLE (Practice Innovation and Clinical Excellence) Registry. We examined associations between patient …
Performance Of Machine Learning Classifiers In Classifying Stunting Among Under-Five Children In Zambia, Obvious Nchimunya Chilyabanyama, Roma Chilengi, Roma Chilengi, Michelo Simuyandi, Caroline C. Chisenga, Masuzyo Chirwa, Kalongo Hamusonde, Rakesh Kumar Saroj, Najeeha Talat Iqbal, Innocent Ngaruye
Performance Of Machine Learning Classifiers In Classifying Stunting Among Under-Five Children In Zambia, Obvious Nchimunya Chilyabanyama, Roma Chilengi, Roma Chilengi, Michelo Simuyandi, Caroline C. Chisenga, Masuzyo Chirwa, Kalongo Hamusonde, Rakesh Kumar Saroj, Najeeha Talat Iqbal, Innocent Ngaruye
Department of Paediatrics and Child Health
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. …
Artificial Intelligence And Machine Learning For Early Detection And Diagnosis Of Colorectal Cancer In Sub-Saharan Africa, Akbar K. Waljee, Eileen M. Weinheimer-Haus, Amina Abubakar, Anthony Ngugi, Geoffrey H. Siwo, Gifty Kwakye, Amit G. Singal, Arvind Rao, Christopher Opio, Mansoor Saleh
Artificial Intelligence And Machine Learning For Early Detection And Diagnosis Of Colorectal Cancer In Sub-Saharan Africa, Akbar K. Waljee, Eileen M. Weinheimer-Haus, Amina Abubakar, Anthony Ngugi, Geoffrey H. Siwo, Gifty Kwakye, Amit G. Singal, Arvind Rao, Christopher Opio, Mansoor Saleh
Institute for Human Development
No abstract provided.
Understanding Deep Learning - Challenges And Prospects, Niha Adnan, Fahad Umer
Understanding Deep Learning - Challenges And Prospects, Niha Adnan, Fahad Umer
Department of Surgery
The developments in Artificial Intelligence have been on the rise since its advent. The advancements in this field have been the innovative research area across a wide range of industries, making its incorporation in dentistry inevitable. Artificial Intelligence techniques are making serious progress in the diagnostic and treatment planning aspects of dental clinical practice. This will ultimately help in the elimination of subjectivity and human error that are often part of radiographic interpretations, and will improve the overall efficiency of the process. The various types of Artificial Intelligence algorithms that exist today make the understanding of their application quite complex. …