Publications

  1. Zolnoori M, Williams MD, Angstman KB, Patel S, Ngufor C, Wi C, Leasure WB. Emergency Department Risk Model: Timely Identification of Patients for Outpatient Care Coordination Model The American Journal of Managed Care. 2024.
  2. Xiao Y, Enayati M, Schaeferle GM, Lanpher BC, Klee EW, Ngufor C. Enhancing Patient Care in Rare Genetic Diseases: An HPO-based Phenotyping Pipeline 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2023; 2754-2760.
  3. Quiram BJ, Killian JM, Redfield MM, Smith J, Hickson LJ, Schulte PJ, Ngufor C, Dunlay SM. Changes in Kidney Function After Diagnosis of Advanced Heart Failure. J Card Fail. 2023 Dec; 29 (12):1617-1625 Epub 2023 July 13
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  4. McCoy RG, Faust L, Heien HC, Patel S, Caffo B, Ngufor C. Longitudinal trajectories of glycemic control among U.S. Adults with newly diagnosed diabetes. Diabetes Res Clin Pract. 2023 Nov; 205:110989 Epub 2023 Nov 02
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  5. Hurley NC, Dhruva SS, Desai NR, Ross JR, Ngufor CG, Masoudi F, Krumholz HM, Mortazavi BJ. Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation. ACM Trans Comput Healthc. 2023 Oct; 4 (4):1-18 Epub 2023 Sept 13
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  6. Ngufor C, Yao X, Inselman JW, Ross JS, Dhruva SS, Graham DJ, Lee JY, Siontis KC, Desai NR, Polley E, Shah ND, Noseworthy PA. Identifying treatment heterogeneity in atrial fibrillation using a novel causal machine learning method. Am Heart J. 2023 Jun; 260:124-140 Epub 2023 Mar 07
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  7. Inselman JW, Jeffery MM, Maddux JT, Lam RW, Shah ND, Rank MA, Ngufor CG. A prediction model for asthma exacerbations after stopping asthma biologics. Ann Allergy Asthma Immunol. 2023 Mar; 130 (3):305-311 Epub 2022 Dec 09
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  8. Farhadi A, Chen D, McCoy R, Scott C, Ma P, Vachon CM, Zhang J, Ngufor C, Miller JA. Classification using deep transfer learning on structured healthcare data. 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023. 2023; 1560-5
  9. Onishchenko D, Marlowe RJ, Ngufor CG, Faust LJ, Limper AH, Hunninghake GM, Martinez FJ, Chattopadhyay I. Screening for idiopathic pulmonary fibrosis using comorbidity signatures in electronic health records. Nat Med. 2022 Oct; 28 (10):2107-2116 Epub 2022 Sept 29
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  10. Enayati M, Zanjirani N, Scott C, Bos JM, Yao X, Ngufor C, Ackerman MJ, Arruda-Olson A. Unsupervised Clustering of Sparse Echo Data to Identify Patients for Implantation of Cardioverter-Defibrillator Proceedings of the 2022 Design of Medical Devices Conference, DMD 2022 Article V001T01A008 (Proceedings of the 2022 Design of Medical Devices Conference, DMD 2022). American Society of Mechanical Engineers. https://doi.org/10.1115/DMD2022-1074. 2022.
  11. Dunlay SM, Blecker S, Schulte PJ, Redfield MM, Ngufor CG, Glasgow A. Identifying Patients With Advanced Heart Failure Using Administrative Data. Mayo Clin Proc Innov Qual Outcomes. 2022 Apr; 6 (2):148-155 Epub 2022 Mar 29
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  12. Shazly SA, Trabuco EC, Ngufor CG, Famuyide AO. Introduction to Machine Learning in Obstetrics and Gynecology. Obstet Gynecol. 2022 Apr 1; 139 (4):669-679 Epub 2022 Mar 10
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  13. Fortune E, Cloud-Biebl BA, Madansingh SI, Ngufor CG, Van Straaten MG, Goodwin BM, Murphree DH, Zhao KD, Morrow MM. Estimation of manual wheelchair-based activities in the free-living environment using a neural network model with inertial body-worn sensors. J Electromyogr Kinesiol. 2022 Feb; 62:102337 Epub 2019 July 17
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  14. Shazly SA, Borah BJ, Ngufor CG, Torbenson VE, Theiler RN, Famuyide AO. Impact of labor characteristics on maternal and neonatal outcomes of labor: A machine-learning model. PLoS One. 2022; 17(8):e0273178. Epub 2022 Aug 22.
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  15. Cai C, Tafti AP, Ngufor C, Zhang P, Xiao P, Dai M, Liu H, Noseworthy P, Chen M, Friedman PA, Cha YM. Using ensemble of ensemble machine learning methods to predict outcomes of cardiac resynchronization. J Cardiovasc Electrophysiol. 2021 Sep; 32 (9):2504-2514 Epub 2021 July 27
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  16. Manemann SM, St Sauver JL, Liu H, Larson NB, Moon S, Takahashi PY, Olson JE, Rocca WA, Miller VM, Therneau TM, Ngufor CG, Roger VL, Zhao Y, Decker PA, Killian JM, Bielinski SJ. Longitudinal cohorts for harnessing the electronic health record for disease prediction in a US population. BMJ Open. 2021 Jun 8; 11 (6):e044353 Epub 2021 June 08
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  17. Herrin J, Abraham NS, Yao X, Noseworthy PA, Inselman J, Shah ND, Ngufor C. Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment. JAMA Netw Open. 2021 May 3; 4 (5):e2110703 Epub 2021 May 03
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  18. Dhruva SS, Ross JS, Mortazavi BJ, Hurley NC, Krumholz HM, Curtis JP, Berkowitz AP, Masoudi FA, Messenger JC, Parzynski CS, Ngufor CG, Girotra S, Amin AP, Shah ND, Desai NR. Use of Mechanical Circulatory Support Devices Among Patients With Acute Myocardial Infarction Complicated by Cardiogenic Shock. JAMA Netw Open. 2021 Feb 1; 4 (2):e2037748 Epub 2021 Feb 01
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  19. Zolnoori M, Williams MD, Leasure WB, Angstman KB, Ngufor C. A Systematic Framework for Analyzing Observation Data in Patient-Centered Registries: Case Study for Patients With Depression. JMIR Res Protoc. 2020 Oct 29; 9 (10):e18366
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  20. Yao X, Inselman JW, Ross JS, Izem R, Graham DJ, Martin DB, Thompson AM, Ross Southworth M, Siontis KC, Ngufor CG, Nath KA, Desai NR, Nallamothu BK, Saran R, Shah ND, Noseworthy PA. Comparative Effectiveness and Safety of Oral Anticoagulants Across Kidney Function in Patients With Atrial Fibrillation. Circ Cardiovasc Qual Outcomes. 2020 Oct; 13 (10):e006515 Epub 2020 Oct 05
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  21. Abraham NS, Yang EH, Noseworthy PA, Inselman J, Yao X, Herrin J, Sangaralingham LR, Ngufor C, Shah ND. Fewer gastrointestinal bleeds with ticagrelor and prasugrel compared with clopidogrel in patients with acute coronary syndrome following percutaneous coronary intervention. Aliment Pharmacol Ther. 2020 Aug; 52 (4):646-654 Epub 2020 July 13
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  22. Chopra S, Morrow MM, Ngufor C, Fortune E. Differences in Physical Activity and Sedentary Behavior Patterns of Postmenopausal Women with Normal versus Low Total Hip Bone Mineral Density Frontiers in Sports and Active Living. 2020.
  23. Ngufor C, Caraballo PJ, O'Byrne TJ, Chen D, Shah ND, Pruinelli L, Steinbach M, Simon G. Development and Validation of a Risk Stratification Model Using Disease Severity Hierarchy for Mortality or Major Cardiovascular Event. JAMA Netw Open. 2020 Jul 1; 3 (7):e208270 Epub 2020 July 01
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  24. Madansingh SI, Ngufor CG, Fortune E. Quality over quantity: skeletal loading intensity plays a key role in understanding the relationship between physical activity and bone density in postmenopausal women. Menopause. 2020 Apr; 27 (4):444-449
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  25. Dhruva SS, Ross JS, Mortazavi BJ, Hurley NC, Krumholz HM, Curtis JP, Berkowitz A, Masoudi FA, Messenger JC, Parzynski CS, Ngufor C, Girotra S, Amin AP, Shah ND, Desai NR. Association of Use of an Intravascular Microaxial Left Ventricular Assist Device vs Intra-aortic Balloon Pump With In-Hospital Mortality and Major Bleeding Among Patients With Acute Myocardial Infarction Complicated by Cardiogenic Shock. JAMA. 2020 Feb 25; 323 (8):734-745
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  26. Abraham NS, Noseworthy PA, Inselman J, Herrin J, Yao X, Sangaralingham LR, Cornish G, Ngufor C, Shah ND. Risk of Gastrointestinal Bleeding Increases With Combinations of Antithrombotic Agents and Patient Age. Clin Gastroenterol Hepatol. 2020 Feb; 18 (2):337-346.e19 Epub 2019 May 18
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  27. Chopra S, Morrow MM, Ngufor C, Fortune E. Differences in Physical Activity and Sedentary Behavior Patterns of Postmenopausal Women With Normal vs. Low Total Hip Bone Mineral Density. Front Sports Act Living. 2020; 2:83 Epub 2020 July 09
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  28. Goyal A, Ngufor C, Kerezoudis P, McCutcheon B, Storlie C, Bydon M. Can machine learning algorithms accurately predict discharge to nonhome facility and early unplanned readmissions following spinal fusion? Analysis of a national surgical registry. J Neurosurg Spine. 2019 Oct 1; 31 (4):568-578 Epub 2019 June 07
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  29. Farhadi A, Chen D, McCoy R, Scott C, Miller JA, Vachon CM, Ngufor C. Breast cancer classification using deep transfer learning on structured healthcare data Proceedings - 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019. 2019 Oct; 277-86
  30. Chen D, Goyal G, Go RS, Parikh SA, Ngufor CG. Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia. JCO Clin Cancer Inform. 2019 May; 3:1-11
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  31. Ngufor C, Van Houten H, Caffo BS, Shah ND, McCoy RG. Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c. J Biomed Inform. 2019 Jan; 89:56-67 Epub 2018 Sept 04
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  32. Murphree DH, Arabmakki E, Ngufor C, Storlie CB, McCoy RG. Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes. Comput Biol Med. 2018 Dec 1; 103:109-115 Epub 2018 Oct 16
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  33. Murphree DH, Quest DJ, Allen RM, Ngufor C, Storlie CB. Deploying Predictive Models In A Healthcare Environment - An Open Source Approach. Conf Proc IEEE Eng Med Biol Soc. 2018 Jul; 2018:6112-6116
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  34. Chen D, Goyal G, Go R, Parikh S, Ngufor C. Predicting time to first treatment in chronic lymphocytic leukemia using machine learning survival and classification methods Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018. 2018; 407-8
  35. McCoy RG, Ngufor C, Van Houten HK, Caffo B, Shah ND. Trajectories of Glycemic Change in a National Cohort of Adults With Previously Controlled Type 2 Diabetes. Med Care. 2017 Nov; 55 (11):956-964
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  36. Ngufor C, Warner MA, Murphree DH, Liu H, Carter R, Storlie CB, Kor DJ. Multitask LS-SVM for Predicting Bleeding and Re-operation due to Bleeding. Healthcare Informatics (ICHI), 2017 IEEE International Conference on. 2017; 56-65.
  37. Upadhyaya SG, Murphree DH Jr, Ngufor CG, Knight AM, Cronk DJ, Cima RR, Curry TB, Pathak J, Carter RE, Kor DJ. Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility. Mayo Clin Proc Innov Qual Outcomes. 2017 Jul; 1 (1):100-110 Epub 2017 Apr 28
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  38. Murphree DH, Kinard TN, Khera N, Storlie CB, Ngufor C, Upadhyaya S, Pathak J, Fortune E, Jacob EK, Carter RE, Poterack KA, Kor DJ. Measuring the impact of ambulatory red blood cell transfusion on home functional status: study protocol for a pilot randomized controlled trial. Trials. 2017 Mar 31; 18 (1):153
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  39. Ngufor C, Warner MA, Murphree DH, Liu H, Carter R, Storlie CB, Kor DJ. Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering. AMIA Annu Symp Proc. 2017; 2017:1332-1341 Epub 2018 Apr 16
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  40. Che Ngufor, Janusz Wojtusiak. Extreme logistic regression Advances in Data Analysis and Classification.2016;10:(1):27-52.
  41. Ngufor C, Murphree D, Upadhyaya S, Madde N, Pathak J, Carter R, Kor D. Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion. AMIA Annu Symp Proc. 2016; 2016:954-963 Epub 2017 Feb 10
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  42. Murphree D, Ngufor C, Upadhyaya S, Madde N, Clifford L, Kor DJ, Pathak J. Ensemble learning approaches to predicting complications of blood transfusion. Conf Proc IEEE Eng Med Biol Soc. 2015 Aug; 2015:7222-5.
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  43. Ngufor C, Upadhyaya S, Murphree D, Madde N, Kor D, Pathak J. A heterogeneous multi-task learning for predicting RBC transfusion and perioperative outcomes Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015; 9105:287-97. Epub 1900 Jan 01.
  44. Ngufor C, Murphree D, Upadhyaya S, Madde N, Kor D, Pathak J. Effects of Plasma Transfusion on Perioperative Bleeding Complications: A Machine Learning Approach. Stud Health Technol Inform. 2015; 216:721-5
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  45. Ngufor C, Upadhyaya S, Murphree D, Kor D, Pathak J. Multi-task learning with selective cross-task transfer for predicting bleeding and other important patient outcomes Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015. 2015; 7344836. Epub 1900 Jan 01.
  46. Murphree DH, Clifford L, Lin Y, Madde N, Ngufor C, Upadhyaya S, Pathak J, Kor DJ. Predicting adverse reactions to blood transfusion Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015. 2015; 82-9.
  47. Murphree DH, Clifford L, Lin Y, Madde N, Ngufor C, Upadhyaya S, Pathak J, Kor DJ. A clinical decision support system for preventing adverse reactions to blood transfusion Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015. 2015; 100-4.
  48. Ngufor C, Wojtusiak J, Pathak J. A systematic prediction of adverse drug reactions using pre-clinical drug characteristics and spontaneous reports Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015. 2015; 76-81.
  49. Che Ngufor, Janusz Wojtusiak. Learning from large distributed data: A scaling down sampling scheme for efficient data processing. International Journal of Machine Learning and Computing (IJMLC) .2014;4:(3):216-224.
  50. 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. In Proceedings of the The 27th International Florida Artificial Intelligence Research Society Conference.2014;FLAIRS-27:
  51. Che Ngufor, Janusz Wojtusiak. Learning from large-scale distributed health data: An approximate logistic regression approach. International Conference on Machine Learning (ICML): Role of Machine Learning in Transforming Healthcare. 2013.
  52. Che Ngufor, Janusz Wojtusiak. Unsupervised labeling of data for supervised learning and its application to medical claims prediction. Computer Science.2013;14:(2):191.
  53. Janusz Wojtusiak, Che Ngufor, John Shiver, Ronald Ewald. Rule-based prediction of medical claims' payments: A method and initial application to medicaid data Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on.2011;2:162-167.
  54. Sabine Le Borne, Che Ngufor. An implicit approximate inverse preconditioner for saddle point problems Electronic Transactions on Numerical Analysis.2010;37:173-188.