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2020 – today
- 2023
[j6]Nathan C. Hurley
, Sanket S. Dhruva, Nihar Desai, Joseph R. Ross, Che Ngufor, Frederick Masoudi, Harlan M. Krumholz, Bobak J. Mortazavi:
Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation. ACM Trans. Comput. Heal. 4(4): 21:1-21:18 (2023)- [c24]Yao Xiao, Moein Enayati, Gavin M. Schaeferle, Brendan C. Lanpher, Eric W. Klee, Che Ngufor:
Enhancing Patient Care in Rare Genetic Diseases: An HPO-based Phenotyping Pipeline. BIBM 2023: 2754-2760 - [c23]Ayda Farhadi, David Chen, Rozalina G. McCoy, Christopher Scott, Ping Ma, Celine M. Vachon, Jingyi Zhang, Che Ngufor, John A. Miller:
Classification Using Deep Transfer Learning on Structured Healthcare Data. SSCI 2023: 1560-1565
2010 – 2019
- 2019
- [j5]Che Ngufor, Holly Van Houten, Brian S. Caffo, Nilay D. Shah, Rozalina G. McCoy:
Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c. J. Biomed. Informatics 89: 56-67 (2019) - [j4]Feichen Shen, Vipin Chaudhary, Yan Liu, Che Ngufor, Hongfang Liu:
Special Issue on Healthcare Knowledge Discovery and Management. J. Heal. Informatics Res. 3(2): 157-158 (2019) - [c22]David Chen, Christopher Scott, Christina L. Luong, Itzhak Z. Attia, Che Ngufor, Adelaide M. Arruda-Olson, Patricia A. Pellikka:
Ensemble Imputation for Healthcare Data. AMIA 2019 - [c21]Che Ngufor, Pedro J. Caraballo, Thomas J. O'Byrne, David Chen, Nilay D. Shah, Michael S. Steinbach, György J. Simon:
A new representation of disease conditions and treatment pathways accurately predicts mortality and chronic diseases. AMIA 2019 - [c20]Thomas J. O'Byrne, M. Regina Castro, Che Ngufor, György J. Simon, Pedro J. Caraballo:
Using Electronic Health Record Data to Identify Patients with Prediabetes. AMIA 2019 - [c19]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:
Identifying Factors Affecting Drug Discontinuation in Patients with Depression: Text Analysis of Patient Drug Review Posts. AMIA 2019 - [c18]Akram Farhadi, David Chen, Rozalina G. McCoy, Christopher Scott, John A. Miller, Celine M. Vachon, Che Ngufor:
Breast Cancer Classification using Deep Transfer Learning on Structured Healthcare Data. DSAA 2019: 277-286 - 2018
- [j3]Dennis H. Murphree, Elaheh Arabmakki, Che Ngufor, Curtis B. Storlie, Rozalina G. McCoy:
Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes. Comput. Biol. Medicine 103: 109-115 (2018) - [c17]Dennis H. Murphree, Daniel J. Quest, Ryan M. Allen, Che Ngufor, Curtis B. Storlie:
Deploying Predictive Models In A Healthcare Environment - An Open Source Approach. EMBC 2018: 6112-6116 - [c16]David Chen, Gaurav Goyal, Ronald Go, Sameer Parikh, Che Ngufor:
Predicting Time to First Treatment in Chronic Lymphocytic Leukemia Using Machine Learning Survival and Classification Methods. ICHI 2018: 407-408 - 2017
- [c15]Che Ngufor, Rozalina G. McCoy, Lixia Yao, Lindsey R. Sangaralingham, Shannon M. Dunlay, Nilay D. Shah:
Identification of Clinically Meaningful Clusters of Multi-morbidity in a National Cohort of Adults Using Unsupervised Learning. AMIA 2017 - [c14]Che Ngufor, Matthew A. Warner, Dennis Murphree, Hongfang Liu, Rickey E. Carter, Curtis B. Storlie, Daryl J. Kor:
Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering. AMIA 2017 - [c13]Che Ngufor, Dennis H. Murphree, Sudhindra Upadhyaya, Jyotishman Pathak, Daryl J. Kor:
Multitask LS-Svm for Predicting Bleeding and Re-operation Due to Bleeding. ICHI 2017: 56-65 - [i1]Dennis H. Murphree, Che Ngufor:
Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge. CoRR abs/1703.05235 (2017) - 2016
- [j2]Che Ngufor, Janusz Wojtusiak:
Extreme logistic regression. Adv. Data Anal. Classif. 10(1): 27-52 (2016) - [c12]Che Ngufor, Dennis Murphree, Sudhindra Upadhyaya, Nageswar Madde, Jyotishman Pathak, Rickey E. Carter, Daryl J. Kor:
Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion. AMIA 2016 - 2015
- [b1]Che Ngufor:
Optimal Integration of Machine Learning Models: A Large-Scale Distributed Learning Framework with Application to Systematic Prediction of Adverse Drug Reactions. George Mason University, Fairfax, Virginia, USA, 2015 - [c11]Che Ngufor, Sudhindra Upadhyaya, Dennis Murphree, Nageswar Madde, Daryl J. Kor, Jyotishman Pathak:
A Heterogeneous Multi-Task Learning for Predicting RBC Transfusion and Perioperative Outcomes. AIME 2015: 287-297 - [c10]Che Ngufor, Sudhindra Upadhyaya, Dennis Murphree, Daryl J. Kor, Jyotishman Pathak:
Multi-task learning with selective cross-task transfer for predicting bleeding and other important patient outcomes. DSAA 2015: 1-8 - [c9]Dennis Murphree, Che Ngufor, Sudhindra Upadhyaya, Nageswar Madde, Leanne Clifford, Daryl J. Kor, Jyotishman Pathak:
Ensemble learning approaches to predicting complications of blood transfusion. EMBC 2015: 7222-7225 - [c8]Che Ngufor, Janusz Wojtusiak, Jyotishman Pathak:
A Systematic Prediction of Adverse Drug Reactions Using Pre-clinical Drug Characteristics and Spontaneous Reports. ICHI 2015: 76-81 - [c7]Dennis H. Murphree, Leanne Clifford, Yaxiong Lin, Nagesh Madde, Che Ngufor, Sudhindra Upadhyaya, Jyotishman Pathak, Daryl J. Kor:
Predicting Adverse Reactions to Blood Transfusion. ICHI 2015: 82-89 - [c6]Dennis H. Murphree, Leanne Clifford, Yaxiong Lin, Nagesh Madde, Che Ngufor, Sudhindra Upadhyaya, Jyotishman Pathak, Daryl J. Kor:
A Clinical Decision Support System for Preventing Adverse Reactions to Blood Transfusion. ICHI 2015: 100-104 - [c5]Che Ngufor, Dennis Murphree, Sudhindra Upadhyaya, Nageswar Madde, Daryl J. Kor, Jyotishman Pathak:
Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning Approach. MedInfo 2015: 721-725 - 2014
- [c4]Janusz Wojtusiak, Che Ngufor, Lorens Helmchen, Jack Hadley:
Creating Clinically Homogeneous Groups of Prostate Cancer Patients. AMIA 2014 - [c3]Che Ngufor, Janusz Wojtusiak, Andrea Hooker, Talha Oz, Jack Hadley:
Extreme Logistic Regression: A Large Scale Learning Algorithm with Application to Prostate Cancer Mortality Prediction. FLAIRS 2014 - 2013
- [j1]Che Ngufor, Janusz Wojtusiak:
Unsupervised Labeling of Data for Supervised Learning and its Application to Medical claims Prediction. Comput. Sci. 14(2): 191-214 (2013) - [c2]Talha Oz, Che Ngufor, Janusz Wojtusiak:
Mining Progress Notes for Prediction of Activities of Daily Living. AMIA 2013 - 2011
- [c1]Janusz Wojtusiak, Che Ngufor, John Shiver, Ronald Ewald:
Rule-Based Prediction of Medical Claims' Payments: A Method and Initial Application to Medicaid Data. ICMLA (2) 2011: 162-167
Coauthor Index
aka: Dennis H. Murphree
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