Rule-Based Prediction of Medical Claims' Payments: A Method and Initial Application to Medicaid Data. - Janusz Wojtusiak; Che Ngufor; John Shiver; Ronald Ewald (ICMLA (2), 2011)

Mining Progress Notes for Prediction of Activities of Daily Living. - Talha Oz; Che Ngufor; Janusz Wojtusiak (AMIA, 2013)

Unsupervised Labeling of Data for Supervised Learning and its Application to Medical claims Prediction. - Che Ngufor; Janusz Wojtusiak (Comput. Sci., 2013)

Creating Clinically Homogeneous Groups of Prostate Cancer Patients. - Janusz Wojtusiak; Che Ngufor; Lorens Helmchen; Jack Hadley (AMIA, 2014)

Extreme Logistic Regression: A Large Scale Learning Algorithm with Application to Prostate Cancer Mortality Prediction. - Che Ngufor; Janusz Wojtusiak; Andrea Hooker; Talha Oz; Jack Hadley (FLAIRS, 2014)

A Heterogeneous Multi-Task Learning for Predicting RBC Transfusion and Perioperative Outcomes. - Che Ngufor; Sudhindra Upadhyaya; Dennis Murphree; Nageswar Madde; Daryl J. Kor; Jyotishman Pathak (AIME, 2015)

Multi-task learning with selective cross-task transfer for predicting bleeding and other important patient outcomes. - Che Ngufor; Sudhindra Upadhyaya; Dennis Murphree; Daryl J. Kor; Jyotishman Pathak (DSAA, 2015)

Ensemble learning approaches to predicting complications of blood transfusion. - Dennis Murphree; Che Ngufor; Sudhindra Upadhyaya; Nageswar Madde; Leanne Clifford; Daryl J. Kor; Jyotishman Pathak (EMBC, 2015)

Predicting Adverse Reactions to Blood Transfusion. - Dennis H. Murphree; Leanne Clifford; Yaxiong Lin; Nagesh Madde; Che Ngufor; Sudhindra Upadhyaya; Jyotishman Pathak; Daryl J. Kor (ICHI, 2015)

A Clinical Decision Support System for Preventing Adverse Reactions to Blood Transfusion. - Dennis H. Murphree; Leanne Clifford; Yaxiong Lin; Nagesh Madde; Che Ngufor; Sudhindra Upadhyaya; Jyotishman Pathak; Daryl J. Kor (ICHI, 2015)

A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports. - Che Ngufor; Janusz Wojtusiak; Jyotishman Pathak (ICHI, 2015)

Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning Approach. - Che Ngufor; Dennis Murphree; Sudhindra Upadhyaya; Nageswar Madde; Daryl J. Kor; Jyotishman Pathak (MedInfo, 2015)

Optimal Integration of Machine Learning Models: A Large-Scale Distributed Learning Framework with Application to Systematic Prediction of Adverse Drug Reactions. - Che Ngufor (2015)

Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion. - Che Ngufor; Dennis Murphree; Sudhindra Upadhyaya; Nageswar Madde; Jyotishman Pathak; Rickey E. Carter; Daryl J. Kor (AMIA, 2016)

Extreme logistic regression. - Che Ngufor; Janusz Wojtusiak (Adv. Data Anal. Classif., 2016)

Identification of Clinically Meaningful Clusters of Multi-morbidity in a National Cohort of Adults Using Unsupervised Learning. - Che Ngufor; Rozalina G. McCoy; Lixia Yao; Lindsey R. Sangaralingham; Shannon M. Dunlay; Nilay D. Shah (AMIA, 2017)

Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering. - Che Ngufor; Matthew A. Warner; Dennis Murphree; Hongfang Liu; Rickey E. Carter; Curtis B. Storlie; Daryl J. Kor (AMIA, 2017)

Multitask LS-Svm for Predicting Bleeding and Re-operation Due to Bleeding. - Che Ngufor; Dennis H. Murphree; Sudhindra Upadhyaya; Jyotishman Pathak; Daryl J. Kor (ICHI, 2017)

Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge. - Dennis H. Murphree; Che Ngufor (CoRR, 2017)

Deploying Predictive Models In A Healthcare Environment - An Open Source Approach. - Dennis H. Murphree; Daniel J. Quest; Ryan M. Allen; Che Ngufor; Curtis B. Storlie (EMBC, 2018)

Predicting Time to First Treatment in Chronic Lymphocytic Leukemia Using Machine Learning Survival and Classification Methods. - David Chen 003; Gaurav Goyal; Ronald Go; Sameer Parikh; Che Ngufor (ICHI, 2018)

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes. - Dennis H. Murphree; Elaheh Arabmakki; Che Ngufor; Curtis B. Storlie; Rozalina G. McCoy (Comput. Biol. Medicine, 2018)

Ensemble Imputation for Healthcare Data. - David Chen 003; Christopher Scott; Christina L. Luong; Itzhak Z. Attia; Che Ngufor; Adelaide M. Arruda-Olson; Patricia A. Pellikka (AMIA, 2019)

A new representation of disease conditions and treatment pathways accurately predicts mortality and chronic diseases. - Che Ngufor; Pedro J. Caraballo; Thomas J. O'Byrne; David Chen 003; Nilay D. Shah; Michael S. Steinbach; György J. Simon (AMIA, 2019)

Using Electronic Health Record Data to Identify Patients with Prediabetes. - Thomas J. O'Byrne; M. Regina Castro; Che Ngufor; György J. Simon; Pedro J. Caraballo (AMIA, 2019)

Identifying Factors Affecting Drug Discontinuation in Patients with Depression: Text Analysis of Patient Drug Review Posts. - Maryam Zolnoori; Che Ngufor; Anthony Faiola; Christina Eldredge; Jake Luo; Sunghwan Sohn; Joyce E. Balls-Berry; Ahmad P. Tafti; Nilay D. Shah; Timothy B. Patrick (AMIA, 2019)

Breast Cancer Classification using Deep Transfer Learning on Structured Healthcare Data. - Akram Farhadi; David Chen 003; Rozalina G. McCoy; Christopher Scott; John A. Miller 001; Celine M. Vachon; Che Ngufor (DSAA, 2019)

Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c. - Che Ngufor; Holly Van Houten; Brian S. Caffo; Nilay D. Shah; Rozalina G. McCoy (J. Biomed. Informatics, 2019)

Special Issue on Healthcare Knowledge Discovery and Management. - Feichen Shen; Vipin Chaudhary; Yan Liu; Che Ngufor; Hongfang Liu (J. Heal. Informatics Res., 2019)

Enhancing Patient Care in Rare Genetic Diseases: An HPO-based Phenotyping Pipeline. - Yao Xiao; Moein Enayati; Gavin M. Schaeferle; Brendan C. Lanpher; Eric W. Klee; Che Ngufor (BIBM, 2023)

Classification Using Deep Transfer Learning on Structured Healthcare Data. - Ayda Farhadi; David Chen 003; Rozalina G. McCoy; Christopher Scott; Ping Ma 001; Celine M. Vachon; Jingyi Zhang 004; Che Ngufor; John A. Miller 001 (SSCI, 2023)

Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation. - Nathan C. Hurley; Sanket S. Dhruva; Nihar Desai; Joseph R. Ross; Che Ngufor; Frederick Masoudi; Harlan M. Krumholz; Bobak J. Mortazavi (ACM Trans. Comput. Heal., 2023)