Dr. Sheng-Chieh Lu | Machine learning | Best Researcher Award
University of Texas MD Anderson Cancer Center | United States
Dr. Sheng-Chieh Lu is a data-driven nursing scientist and healthcare informatics expert, currently serving as a Data Scientist in the Department of Symptom Research at The University of Texas MD Anderson Cancer Center. He earned his BS in Nursing and MS in Medical Informatics from National Yang-Ming University, Taiwan, and completed his PhD in Nursing at the University of Minnesota in 2020. His doctoral research focused on the evaluation of integrative health interventions using data science approaches.
Profile:
Educational Background:
Dr. Sheng-Chieh Lu earned his Bachelor of Science in Nursing and Master of Science in Medical Informatics from National Yang-Ming University in Taiwan. He completed his PhD in Nursing at the University of Minnesota in 2020 under the mentorship of Dr. Karen A. Monsen and Dr. Connie White Delaney. His dissertation focused on data-driven evaluation of integrative health interventions in community-based care.
Professional Licenses and Certifications:
Dr. Lu is a Registered Nurse (Taiwan) and holds certifications including the Primary Certificate of Informatics Nurse and Primary Emergency Medical Technician.
Academic and Professional Positions:
Dr. Lu currently serves as a Data Scientist at the MD Anderson Cancer Center, where he previously held positions as a Postdoctoral Fellow and Computational Scientist. He is also an Affiliate Faculty Member at the University of Minnesota School of Nursing. His past roles include Nursing Informatics Specialist at En Chu Kong Hospital and Adjunction Lecturer at Yuanpei University of Medical Technology in Taiwan.
In 2023, he was appointed Review Editor for Frontiers in Digital Health, reflecting his active role in academic publishing and peer review.
Research Interests and Contributions:
Dr. Lu’s research integrates nursing, informatics, data science, and machine learning to enhance healthcare delivery and outcomes. His contributions span topics such as cancer symptom management, immunotherapy toxicity prediction, robotic bronchoscopy diagnostics, and the application of large language models (LLMs) in patient-reported outcome measurement.
He has served in multiple roles, including principal investigator, data scientist, and collaborator on diverse projects involving electronic health records (EHRs), clinical decision support systems, and mHealth applications. His dissertation and subsequent studies have significantly contributed to the advancement of integrative and community-based care models.
Memberships and Editorial Service:
Dr. Lu is a member of the American Medical Informatics Association, Midwest Nursing Research Society, Taiwan Nurses Association, and Taiwan Nursing Informatics Association. He is a Review Editor for Frontiers in Digital Health and previously served as Student and Adjunction Co-director of the Omaha System Partnership.
Honors and Scholarships:
Dr. Lu has been recognized with several prestigious fellowships and scholarships, including:
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Marilee A. Miller Fellowship in Educational Leadership (2017–2018)
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Connie White Delaney Fellowship in Nursing Innovation (2017–2018)
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Beatrice L. Witt Endowment Fund (2016–2017)
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Violet A. Shea Nursing Scholarship (2016–2017)
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Council of Agriculture Scholarship (2007–2011)
Citation Metrics:
Publication Top Notes:
Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison
2022
Citations: 75
On the importance of Interpretable Machine Learning Predictions to Inform Clinical Decision Making in Oncology
2023
Citations: 69
Machine learning–based short-term mortality prediction models for patients with cancer using electronic health record data: systematic review and critical appraisal
2022
Citations: 42
Novel machine learning approach for the prediction of hernia recurrence, surgical complication, and 30-day readmission after abdominal wall reconstruction
2022
Citations: 39
Using ADDIE model to develop a nursing information system training program for new graduate nurse
2016
Citations: 39