ArticleKorean journal of radiology2024
How to Optimize Prompting for Large Language Models in Clinical Research.
Article in Korean journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Prospective quantitative analysis of hyperparameter and input optimization in GPT-5: comparative contribution to radiologist performance in abdominal radiology.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Article
- Article
- Invited Commentary on Comparative Evaluation of Proprietary and Open-Source Large Language Models for Systematic Multi-source Information Extraction in Interventional Oncology.Cardiovascular and interventional radiology · 2026Article
- Applications of Large Language Models in Medical Research: From Systematic Reviews to Clinical Studies.Bioengineering (Basel, Switzerland) · 2026Review
- Insufficient reporting quality in large language model studies in the field of radiology.Insights into imaging · 2026Article
- Navigating the ethical landscape of scholarly publishing: a comparative evaluation of Gemini and DeepSeek LLMs in addressing authorship and contributorship disputes.Frontiers in research metrics and analytics · 2026Article
- Performance of large language models in reporting oral health concerns and side effects in head and neck cancer: a comparative study.Journal of cancer research and clinical oncology · 2025Article
- Minimum Reporting Items for Clear Evaluation of Accuracy Reports of Large Language Models in Healthcare (MI-CLEAR-LLM): 2025 Updates.Korean journal of radiology · 2025Review
- Tracing Prescribed Knowledge Flows in Wastewater Management Policies: An AI-Assisted, Governmentality-Informed Framework with Insights from Indonesia.Environmental management · 2025Article
- Uncover This Tech Term: Application Programming Interface for Large Language Models.Korean journal of radiology · 2025Article
- Conversion of Mixed-Language Free-Text CT Reports of Pancreatic Cancer to National Comprehensive Cancer Network Structured Reporting Templates by Using GPT-4.Korean journal of radiology · 2025Article
- Diagnostic performance of multimodal large language models in radiological quiz cases: the effects of prompt engineering and input conditions.Ultrasonography (Seoul, Korea) · 2025Article
- Crucial Role of Understanding in Human-Artificial Intelligence Interaction for Successful Clinical Adoption.Korean journal of radiology · 2025Article
- Minimum Reporting Items for Clear Evaluation of Accuracy Reports of Large Language Models in Healthcare (MI-CLEAR-LLM).Korean journal of radiology · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What 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.