The research of Che G. Ngufor, Ph.D., is centered on the idea that the understanding of patient phenotypes and heterogeneity of treatments across the different disease populations is still limited. This situation persists even though this knowledge is important for clinical and public health efforts to address poor outcomes in areas such as cancer, heart failure, diabetes and obstetrics. Dr. Ngufor uses core multimodal research approaches in data science and artificial intelligence (AI) to disentangle this heterogeneity and improve early prediction of longitudinal disease progressions.
Dr. Ngufor investigates state-of-the-art technologies and develops core machine-learning approaches. He uses statistical learning theory to model and analyze health care data. His goal is to develop and apply core methodologies that leverage structure in multimodality electronic health records (EHRs) and enhance representational power. This will improve accuracy and scalability with theoretical guarantees, demonstrating the effectiveness of the learning strategy.
Dr. Ngufor's research program focuses on developing end-to-end AI and machine-learning solutions for descriptive, causal, predictive and prescriptive analytics with the goal of optimizing clinical decisions and interventions.
- AI-powered digital health.
- Patient-centered remote monitoring. Dr. Ngufor aims to provide advanced AI tools to monitor, interrogate and analyze patient disease and symptom progression. Such tools will allow health care providers to interact virtually with patients to modify care plans, educate patients about their health conditions and engage with patients to provide the best possible care.
- Wearable health sensors. Continuous and real-time monitoring is essential to provide better care for patients with chronic illnesses such as cancer, cardiovascular diseases, heart failure, diabetes and neurological disorders. Dr. Ngufor aims to develop processes for harvesting heterogeneous wearable sensor data and to create AI tools to accelerate knowledge discovery from these data.
- AI and health disparity. AI is a double-edged sword. AI tools can be of great benefit in optimizing clinical decisions and interventions but can inadvertently promote health disparity. To promote health equity, Dr. Ngufor is developing strategies that can enable his AI tools to harness factors such as social and societal determinants of health and highlight potential areas to address health disparity.
- AI systems to make pregnancy and labor safer for mothers and newborns. Care during labor and delivery is a uniquely complex and challenging task, in that every obstetrician is caring for two patients simultaneously — both mother and baby. Sophisticated, real-time, data-driven, AI-powered digital health solutions can help obstetricians address the unique needs of the mother and baby and achieve better outcomes. Dr. Ngufor aims to address these needs by integrating robust, adaptable and dynamic AI solutions into labor and delivery units.
- Accelerating precision medicine with AI and virtual or augmented reality. Dr. Ngufor investigates, develops and advances the use of innovative technology such as virtual, augmented or mixed reality, collectively called X-reality, that has the potential to shape the future of health care. He uses X-reality technology to translate and deliver data-driven evidence-based disease management, interventions and education. He also uses it to facilitate virtual practice of learned principles that can promote self-management of health conditions.
Significance to patient care
The emergence of data science and the use of EHRs have transformed modern health care into a data-driven field. This transformation has been accelerated by the synergy of advanced data science and clinical expertise, innovative use of state-of-the-art AI, visualization, and high-performance computation. The biggest benefit of this innovative synergy is in improving patient outcomes, education and engagement as well as empowering patients to take greater control and play active roles in their health care.
Dr. Ngufor's research has resulted in AI-enabled systems, with commercial potential, that unlock clinical evidence embedded in large EHR data. These systems help support treatment decisions, based not only on predicted risk assessment but also on causal inference establishing the expected benefit of an intervention.
- American Medical Informatics Association (AMIA), 2016-present.
- Institute of Electrical and Electronics Engineers (IEEE).
- Member, 2011-present.
- Financial chair, International Conference on Healthcare Informatics, 2022.
- Program director/principal investigator, Establishment of an Inclusive Cancer Care Research Equity (iCCaRE) for Black Men Consortium, Department of Defense, 2022-2024.