ArticleAdvances in neural information processing systems2024
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias.
Article in Advances in neural information processing systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The TRIPOD-LLM reporting guideline for studies using large language models: a Korean translation.Ewha medical journal · 2025Guideline
- Design principles for integrated AI alignment.Patterns (New York, N.Y.) · 2026Review
- A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction.Frontiers in digital health · 2026Review
- Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models.Proceedings of machine learning research · 2025Article
- Reliability of Large Language Model Knowledge Across Brand and Generic Cancer Drug Names.JCO clinical cancer informatics · 2025Article
- Foundation model embeddings for quantitative tumor imaging biomarkers.Research square · 2025Article
- Retrieval-augmented generation for generative artificial intelligence in health care.npj health systems · 2025Review
- The TRIPOD-LLM reporting guideline for studies using large language models.Nature medicine · 2025Review
- Improving Patient Engagement: Is There a Role for Large Language Models?International journal of radiation oncology, biology, physics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data. In this study, we introduce
Identifiers
40313683PMC12045606What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.