Che Ngufor

According to our database, Che Ngufor authored at least 32 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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., October, 2023

Classification Using Deep Transfer Learning on Structured Healthcare Data.

Ayda Farhadi, David Chen, Rozalina G. McCoy, Christopher Scott, Ping Ma, Celine M. Vachon, Jingyi Zhang, Che Ngufor, John A. Miller

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

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

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2019

Special Issue on Healthcare Knowledge Discovery and Management.

Feichen Shen, Vipin Chaudhary, Yan Liu, Che Ngufor, Hongfang Liu

J. Heal. Informatics Res., 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

Breast Cancer Classification using Deep Transfer Learning on Structured Healthcare Data.

Akram Farhadi, David Chen, Rozalina G. McCoy, Christopher Scott, John A. Miller, Celine M. Vachon, Che Ngufor

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 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

Proceedings of the AMIA 2019, 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

Proceedings of the AMIA 2019, 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, Nilay D. Shah, Michael S. Steinbach, György J. Simon

Proceedings of the AMIA 2019, 2019

Ensemble Imputation for Healthcare Data.

David Chen, Christopher Scott, Christina L. Luong, Itzhak Z. Attia, Che Ngufor, Adelaide M. Arruda-Olson, Patricia A. Pellikka

Proceedings of the AMIA 2019, 2019

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

Predicting Time to First Treatment in Chronic Lymphocytic Leukemia Using Machine Learning Survival and Classification Methods.

David Chen, Gaurav Goyal, Ronald Go, Sameer Parikh, Che Ngufor

Proceedings of the IEEE International Conference on Healthcare Informatics, 2018

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

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

2017

Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge.

Dennis H. Murphree, Che Ngufor

CoRR, 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

Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 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

Proceedings of the AMIA 2017, 2017

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

Proceedings of the AMIA 2017, 2017

2016

Extreme logistic regression.

Che Ngufor, Janusz Wojtusiak

Adv. Data Anal. Classif., 2016

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

Proceedings of the AMIA 2016, 2016

2015

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

Che Ngufor

PhD thesis, 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

Proceedings of the MEDINFO 2015: eHealth-enabled Health, 2015

A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports.

Che Ngufor, Janusz Wojtusiak, Jyotishman Pathak

Proceedings of the 2015 International Conference on Healthcare Informatics, 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

Proceedings of the 2015 International Conference on Healthcare Informatics, 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

Proceedings of the 2015 International Conference on Healthcare Informatics, 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

Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 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

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

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

Proceedings of the Artificial Intelligence in Medicine, 2015

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

Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference, 2014

Creating Clinically Homogeneous Groups of Prostate Cancer Patients.

Janusz Wojtusiak, Che Ngufor, Lorens Helmchen, Jack Hadley

Proceedings of the AMIA 2014, 2014

2013

Unsupervised Labeling of Data for Supervised Learning and its Application to Medical claims Prediction.

Che Ngufor, Janusz Wojtusiak

Comput. Sci., 2013

Mining Progress Notes for Prediction of Activities of Daily Living.

Talha Oz, Che Ngufor, Janusz Wojtusiak

Proceedings of the AMIA 2013, 2013

2011

Rule-Based Prediction of Medical Claims' Payments: A Method and Initial Application to Medicaid Data.

Janusz Wojtusiak, Che Ngufor, John Shiver, Ronald Ewald

Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011