ArticleScience progress
AI-driven patient-centered care: A digital transformation framework for gynecologic cancer genetic counseling.
Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Performance and limitations of four large language models in genetic counseling for thalassemia.Frontiers in digital health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ObjectivesThis study evaluates artificial intelligence (AI) reasoning capabilities in gynecologic cancer genetic counseling, comparing the performance of ChatGPT and DeepSeek models to guide patient-centered AI implementation in clinical genetics.MethodsUsing 40 National Comprehensive Cancer Network-aligned counseling scenarios, we conducted blinded dual-oncologist evaluations of two large language models. Methodological rigor included model anonymization, a pre-calibrated scoring framework, and validated metrics (Global Quality Scale and Patient Education Materials Assessment Tool) assessing informational coherence, understandability, and actionability.ResultsDeepSeek demonstrated superior informational breadth (mean character difference: -609.0,
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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.