August 2, 2025Open Access

SKiM-GPT: Combining Biomedical Literature-Based Discovery with Large Language Model Hypothesis Evaluation

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SKiM-GPT enhances literature-based discovery by integrating large language models for hypothesis evaluation.
It addresses critical gaps such as false-positive leads and lack of biological relationships in LBD systems.
The system achieves strong agreement with expert biologists, indicating reliability in hypothesis testing.
SKiM-GPT is open-source and supports both computational and wet-lab researchers in evaluating biomedical hypotheses.

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SKiM-GPT combines literature-based discovery and large language models, suggesting improved hypothesis evaluation in biomedical research.

Freeman et al. (2025) studied this question.

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