# Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines

Source: [Decision Knowledge Graphs: Construction of and Usage in Question Answering for Clinical Practice Guidelines](<https://www.sota2.com/research/paper/68fa703a1e209131cea49bc0>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:25:24.889Z

Authors: Vasudhan Varma Kandula, Pushpak Bhattacharyya

Published: 2023-08-06T01:38:40.000Z

## Abstract

In the medical domain, several disease treatment procedures have been documented properly as a set of instructions known as Clinical Practice Guidelines (CPGs). CPGs have been developed over the years on the basis of past treatments, and are updated frequently. A doctor treating a particular patient can use these CPGs to know how past patients with similar conditions were treated successfully and can find the recommended treatment procedure. In this paper, we present a Decision Knowledge Graph (DKG) representation to store CPGs and to perform question-answering on CPGs. CPGs are very complex and no existing representation is suitable to perform question-answering and searching tasks on CPGs. As a result, doctors and practitioners have to manually wade through the guidelines, which is inefficient. Representation of CPGs is challenging mainly due to frequent updates on CPGs and decision-based structure. Our proposed DKG has a decision dimension added to a Knowledge Graph (KG) structure, purported to take care of decision based behavior of CPGs. Using this DKG has shown 40\\% increase in accuracy compared to fine-tuned BioBert model in performing question-answering on CPGs. To the best of our knowledge, ours is the first attempt at creating DKGs and using them for representing CPGs.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2308.02984>)

[PDF](<https://arxiv.org/pdf/2308.02984.pdf>)