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A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

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Published on: May 10, 2022

From clinical requirement to personalized wellness decision support: a data-driven framework for computer-supported

Pei-Yun Hsueh¹, Ci-Wei Lan, Vincent Deng

¹IBM T.J. Watson Research Center, USA.

Studies in Health Technology and Informatics

|August 10, 2012

Summary

This study introduces a new data-driven framework for personalized wellness decision support. It maps patient needs to tailored recommendations, improving guideline-based healthcare.

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Published on: December 11, 2016

Area of Science:

Health Informatics
Clinical Decision Support Systems
Personalized Medicine

Background:

Patient-centric healthcare models are increasing, leading to more patient data.
Data-driven analytics improve outcomes but face challenges in guideline-based practice.

Purpose of the Study:

To address the gap in deploying data-driven analytics in guideline-based healthcare.
To present a novel framework for computer-supported guideline refinement.
To map patient guideline requirements to personalized recommendations based on clinical and contextual factors.

Main Methods:

Developed a novel data-driven personalization framework.
Framed the mapping task as a statistical decision problem to maximize expected utility.
Implemented the framework within a clinical decision support system.

Main Results:

The framework effectively produces personalized recommendations.
Recommendations consider both clinical and contextual factors for individual differences.
Demonstrated successful implementation in a guideline-based clinical decision support system.

Conclusions:

The proposed framework enhances personalized wellness decision support.
It bridges the gap between data analytics and guideline-based practice.
Future work will explore opportunities and challenges for broader adoption.