Research graph
References from Performance evaluation of large language models in bladder cancer patient education Q&A: a cross-sectional study. Local targets link to admitted publications; unresolved targets remain external evidence.
Incidence, mortality, and risk factors of bladder, kidney, prostate and testicular cancers in China and comparisons with the United States, the United Kingdom, Japan, and the Republic of Korea: an up-to-date overview based on the Global Burden of Disease 2021
10.1186/s40164-025-00694-9 · 2025 · External reference
Bladder cancer
10.1038/551s33a · 2017 · External reference
Diseases burden and trends of bladder cancer attributable to behavioral and metabolic factors among global and Chinese population, 1990-2021: results from the global burden of disease study 2021
10.1186/s41043-025-01113-9 · 2025 · External reference
Age-sex-specific burden of urological cancers attributable to risk factors in China and its provinces, 1990-2021, and forecasts with scenarios simulation: a systematic analysis for the Global Burden of Disease Study 2021
10.1016/j.lanwpc.2025.101517 · 2025 · External reference
Disease burden of bladder cancer in China and the different SDI regions over the world from 1990 to 2021
10.2139/ssrn.5192801 · 2025 · External reference
ChatGPT vs. Gemini: Which Provides Better Information on Bladder Cancer
10.20944/preprints202412.1528.v1 · 2025 · External reference
Quality and readability of online health information on common urologic cancers: assessing barriers to health literacy in urologic oncology
10.1097/upj.0000000000000574 · 2024 · External reference
Bladder cancer health literacy: assessing readability of online patient education materials
10.3233/blc-200387 · 2021 · External reference
National and subnational trends of years of life lost and reduced life expectancy caused by bladder cancer in China from 2005 to 2020
10.1186/s12889-025-24834-2 · 2025 · External reference
Artificial intelligence improves urologic oncology patient education and counseling
2024 · External reference
What do the current popular artificial intelligence chatbots offer us regarding patient information? Comparison of responses from the ten most popular chatbots about bladder cancer
10.1007/s11764-025-01921-2 · 2025 · External reference
The use of large language models in generating patient education materials: a scoping review
10.5455/aim.2024.33.4-10 · 2025 · External reference
Balancing accuracy and readability: comparative evaluation of AI chatbots for patient education on rotator cuff tears
10.3390/healthcare13212670 · 2025 · External reference
Enhanced artificial intelligence in bladder cancer management: A comparative analysis and optimization study of multiple large language models
10.1089/end.2024.0860 · 2025 · External reference
Bladder cancer, version 1.2026, NCCN clinical practice guidelines in oncology
10.6004/jnccn.2026.0022 · 2026 · External reference
Evaluating AI-generated patient education guides: A comparative study of chatGPT and deepseek
10.7759/cureus.85277 · 2025 · External reference
Evaluation of large language models in patient education for hyperthyroidism: A comparative study of chatgpt, gemini, and deepseek
10.1007/s12020-025-04421-6 · 2025 · External reference
Assessing communicative effectiveness of public health information in chinese: developing automatic decision aids for international health professionals
10.3390/ijerph181910329 · 2021 · External reference
Comparison of Readability Scores for Written Health Information Across Formulas Using Automated vs Manual Measures
10.1001/jamanetworkopen.2022.46051 · 2022 · External reference
GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment
10.1371/journal.pone.0324175 · 2025 · External reference
Artificial intelligence in patient education for androgenetic alopecia: A comparative study of chatGPT, gemini, and deepseek R1
10.5826/dpc.1504a5929 · 2025 · External reference
Improving readability of shoulder and elbow surgery online patient education material with Chat GPT (Chat Generative Pretrained Transformer) 4
10.1016/j.jse.2025.02.025 · 2025 · External reference
Assessing the power of AI: a comparative evaluation of large language models in generating patient education materials in dentistry
10.1038/s41405-025-00349-1 · 2025 · External reference
Performance of large language models on the Turkish Pharmacy Specialty Examination: a comparative analysis of accuracy, confidence, and readability
10.1038/s41598-026-57001-7 · 2026 · External reference
Large language models vs thrombosis experts: a comparative study on patient education and clinical decision-making in venous thromboembolism
10.1016/j.jtha.2025.09.004 · 2026 · External reference
DiaGuide-LLM-Using large language models for patient-specific education and health guidance in diabetes
10.3389/frai.2025.1652556 · 2025 · External reference
Generative AI in consumer health: leveraging large language models for health literacy and clinical safety with a digital health framework
10.3389/fdgth.2025.1616488 · 2025 · External reference
Quality and readability analysis of artificial intelligence-generated medical information related to prostate cancer: a cross-sectional study of ChatGPT and DeepSeek
10.5534/wjmh.250144 · 2025 · External reference
Assessing reading levels of health information: uses and limitations of flesch formula
10.4103/1357-6283.210517 · 2017 · External reference
Perspective: advancing public health education by embedding AI literacy
10.3389/fdgth.2025.1584883 · 2025 · External reference
Development and evaluation of an agentic LLM based RAG framework for evidence-based patient education
10.1136/bmjhci-2025-101570 · 2025 · External reference