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Principal Investigator: BONNIE J MARTIN-HARRIS
Organization: NORTHWESTERN UNIVERSITY
Fiscal Year: 2024
Award: $183,209
Funding agency: National Institute on Deafness and Other Communication Disorders
PROJECT SUMMARY/ABSTRACT
The emergence of electronic medical records, large data registries and readily accessible, protected servers have
resulted in an explosion of digital information with potentially high clinical impact for improving patient
management and outcomes. Big data warehouses that capture standardized information within the scope of
clinical practices allow trained scientists to not only engage in traditional hypothesis testing, but to also
uncover new hypotheses, refine existing theories and apply new discoveries to health assessments and
interventions. Despite the accessibility and potential impact of these data platforms, clinician scientists have
traditionally directed experiments that incorporate relatively small sample sizes and data from individual
laboratories, and have not been trained in big data analytics or in engaging appropriate team scientists who
work in this space, such as computer scientists, biostatisticians and engineers. The overarching goal of this
proposal is to mentor early patient oriented communication and swallowing scientists in big data analytics and
to mentor and involve early data science scholars in communication and swallowing research. The PI proposes
four primary mentorship and research goals in this K24 renewal proposal: 1. Train a cadre of early stage
communication and swallowing scientists in data science methods, including machine learning, by an expert,
interdisciplinary, collaborative data science team, 2. Engage and introduce early career data scientists from
fields of biostatistics, computer science and engineering to communication and swallowing sciences, and
respective data sets, toward facilitating interdisciplinary data science teams and research productivity, 3. Apply
novel data science methods to identify phenotypes of swallowing impairment and severity classifications in
patient groups known to be at high risk for nutritional and health complications related to dysphagia, and 4.
Develop a new area of research in machine learning applications toward improving reliability of physiologic
swallowing assessment. The data science theme of the career development and research plan directly align with
NIDCD's Strategic Plan for Data Science which lists as its mission: Storing, managing, standardizing and
publishing the vast amounts of data produced by biomedical research. NIDCD recognizes that accessible,
well-organized, secure and efficiently operated data resources are critical to modern scientific inquiry…and
by maximizing the value of data generated through NIH-funded efforts, the pace of biomedical discoveries
and medical breakthroughs for better health outcomes can be accelerated.
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