# EQuitable, Uniform and Intelligent Time-based conformal Inference (EQUITI) Framework

> **NIH NIH R01** · EMORY UNIVERSITY · 2022 · $232,169

## Abstract

Project Summary
Sepsis is a major public health challenge caused by a dysfunctional host response to infection, resulting in
multiple organ dysfunction and increased risk of death. In the parent award, we investigate the physiological
mechanisms that contribute to increased likelihood sepsis among patients admitted to the ICU. In this
supplement we evaluate possible causes of uncertainty by utilizing conformal predictions and hypothesis tests.
We will derive a novel framework which we term EQUITI that can be used to characterize the degree to which
the model is uncertain, due to the influence of bias in the data. Furthermore, this supplement will also
contribute workforce and skills development aids that are proposed to be used to improve clinicians and
healthcare professionals understanding of ambiguities in model estimated output. Finally, these aids will also
help health professionals better understand how these uncertainties can be identified and used to improve
individual and team situational awareness.

## Key facts

- **NIH application ID:** 10599622
- **Project number:** 3R01GM139967-02S1
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Rishikesan Kamaleswaran
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $232,169
- **Award type:** 3
- **Project period:** 2021-09-10 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10599622

## Citation

> US National Institutes of Health, RePORTER application 10599622, EQuitable, Uniform and Intelligent Time-based conformal Inference (EQUITI) Framework (3R01GM139967-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10599622. Licensed CC0.

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