Piper Ranallo
University of Minnesota, MN·Computer Science·Early-career
Computers can only help doctors and researchers learn from health records if they can understand what the records mean. For mental health, many key ideas such as symptoms, life stressors, assessment questionnaires and therapies lack precise, machine-readable definitions in standard medical vocabularies.
- Fields
Computer Science
Medicine & Clinical Research
Psychology
- Topics
ontology
clinical terminology
biomedical informatics
- Grants
- 1 known grant, through May 2029
What they work on
- Build machine-readable ontology models that define mental, behavioral and social processes, findings, assessment instruments and interventions, using borderline personality disorder and psychosis as test cases.
- Reach consensus on clinical concepts, terms, definitions and relationships with experts, patients and families, using focus groups, the Nominal Group Technique and the Delphi method.
- Mine electronic health records, published research text and existing terminologies to find mental health concepts missing from current clinical vocabularies.
- Have domain experts evaluate the new terms and models, then share them with publishers of widely adopted clinical terminologies for broad use.
More about the research
That gap makes it hard to apply computational tools and clinical decision support to mental health care.
Why it matters
Standardized, computer-readable definitions of mental health symptoms, assessments and treatments could let health systems and researchers analyze records at scale and build decision-support tools for psychiatric care. People living with conditions such as borderline personality disorder and psychosis could benefit through faster discovery of knowledge and better care delivery.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Shannon E Sauer-Zavala
University of Kentucky, KY·Psychology
Test whether brief therapy modules each change their intended personality dimension (neuroticism, agreeableness or conscientiousness), using single-case experiments with baseline, 6-session treatment and follow-up phases.
Allison Summers
Oregon Health & Science University, OR·Medicine & Clinical Research
Develop large language model pipelines that extract amblyopia treatment, adherence and visual outcome information from free-text ophthalmology clinical notes, where these concepts are documented inconsistently and not in structured EHR fields.
Selen Bozkurt
Emory University, GA·Medicine & Clinical Research
Translate clinical trial protocol eligibility text into computable phenotypes and query packages tied to standard vocabularies, and validate them against expert references and prescreening logs.
The school
University of Minnesota: 88 labs on PI Pages, $1.4B a year on research, 722 research doctorates a year.
Reach out
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