Translational Informatics, Biostatistics and Epidemiology Lab
What do we do?
The Translational Informatics, Biostatistics and Epidemiology laboratory (TIBE Labs) led by Dr. Arthur Owora applies novel biostatistical and machine learning methodologies to different (structured and unstructured) and multiple data sources (active and passive) to generate analytics and insights regarding disease etiology, risk, and prognosis. Through collaboration with clinicians, the TIBE laboratory aims to translate such insights to inform effective clinical decision-making at point-of-care including more proactive and personalized care, for improved patient-centered outcomes in real-world healthcare settings.
Developing a Childhood Asthma Risk Passive Digital Marker
K01HL163462 | Owora (PI) | 12/01/2022-11/30/2026
To develop and determine the usability, acceptability, feasibility, and preliminary efficacy of a childhood asthma Passive Digital Marker (PDM) for early disease detection. Here, a PDM refers to a ML algorithm that can be used to retrieve and synthesize pre-existing ‘Passively’ collected mother/child dyad prognostic data (i.e., medical history) at ages 0-3 years in ‘Digital’ EHR to provide an objective and quantifiable ‘Marker’ of a child’s asthma risk and phenotype at ages 6-10 years.
(* student mentees/advisees)
Chusyd DE, Austad SN, Dickinson SL, Ejima K, Gadbury GL, Golzarri-Arroyo L, Holden RJ, Jamshidi-Naeini Y, Landsittel D, Mehta DT, Oakes JM, Owora AH, Pavela G, Rojo J, Sandel MW, Smith DL, Vorland CJ, Xun P, Zoh R, Allison DB. Randomization, design, and analysis for interdependency in aging research: no person or mouse is an island. Nature Aging. 2022 Dec 22. 2(12): 1101-1111.