Summary of Narrative Feature or Structured Feature? a Study Of Large Language Models to Identify Cancer Patients at Risk Of Heart Failure, by Ziyi Chen et al.
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
by Ziyi Chen, Mengyuan Zhang, Mustafa Mohammed Ahmed, Yi Guo, Thomas J. George, Jiang Bian, Yonghui Wu
First submitted to arxiv on: 18 Mar 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel machine learning approach has been developed to identify cancer patients at risk of heart failure using electronic health records (EHRs). The study compared traditional machine learning models with Time-Aware long short-term memory (T-LSTM) and large language models (LLMs), leveraging novel narrative features derived from structured medical codes. A dataset of 12,806 patients diagnosed with lung, breast, and colorectal cancers was analyzed, including 1,602 individuals who developed heart failure after cancer treatment. The LLM, GatorTron-3.9B, outperformed traditional support vector machines by 39%, T-LSTM by 7%, and BERT by 5.6% in terms of F1 scores. The proposed narrative features significantly increased feature density and improved performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study uses computer programs to help doctors figure out which cancer patients are at risk of getting heart problems after treatment. They looked at a big group of patients with lung, breast, and colon cancers and found that some got heart failure later on. The researchers tested different types of computer models to see which ones were best at predicting who would get heart problems. The winner was a special kind of model called GatorTron-3.9B. This could help doctors keep cancer patients safe from heart troubles. |
Keywords
* Artificial intelligence * Bert * Lstm * Machine learning
