Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
Gary S. Collins, Karel G.M. Moons, Paula Dhiman, et al.
BMJ (2024), pp. e078378-e078378
Open Access | Times Cited: 249

Showing 1-25 of 249 citing articles:

Developing clinical prediction models: a step-by-step guide
Orestis Efthimiou, Michael Seo, Konstantina Chalkou, et al.
BMJ (2024), pp. e078276-e078276
Open Access | Times Cited: 21
Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist
Yilin Ning, Salinelat Teixayavong, Yuqing Shang, et al.
The Lancet Digital Health (2024)
Open Access | Times Cited: 18
The TRIPOD-LLM reporting guideline for studies using large language models
Jack Gallifant, Majid Afshar, Saleem Ameen, et al.
Nature Medicine (2025)
Closed Access | Times Cited: 4
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Alejandro F. Frangi, Antonio R. Porras, et al.
BMJ (2025), pp. e081554-e081554
Open Access | Times Cited: 3
Practical Guide to the Use of AI-Enabled Analytics in Research
Anai N. Kothari, Amy H. Kaji, Genevieve B. Melton
JAMA Surgery (2025)
Closed Access | Times Cited: 1
Artificial intelligence in rheumatology research: what is it good for?
José Miguel Sequí-Sabater, Diego Benavent
RMD Open (2025) Vol. 11, Iss. 1, pp. e004309-e004309
Open Access | Times Cited: 1
Mortality prediction after major surgery in a mixed population through machine learning: a multi‐objective symbolic regression approach
Pietro Arina, Davide Ferrari, Nicholas Tetlow, et al.
Anaesthesia (2025)
Open Access | Times Cited: 1
Risk prediction tools for pressure injury occurrence: an umbrella review of systematic reviews reporting model development and validation methods
Bethany Hillier, Katie Scandrett, April Coombe, et al.
Diagnostic and Prognostic Research (2025) Vol. 9, Iss. 1
Open Access | Times Cited: 1
Explainable machine learning models for identifying mild cognitive impairment in older patients with chronic pain
Xiaoang Zhang, Yu‐Ping Liao, Daying Zhang, et al.
BMC Nursing (2025) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis
Ammar Zaka, Cecil Mustafiz, Daud Mutahar, et al.
Open Heart (2025) Vol. 12, Iss. 1, pp. e002779-e002779
Open Access | Times Cited: 1
Accessible model predicts response in hormone receptor positive HER2 negative breast cancer receiving neoadjuvant chemotherapy
Luca Mastrantoni, Giovanna Garufi, Giulia Giordano, et al.
npj Breast Cancer (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 1
Establishing methodological standards for the development of artificial intelligence-based Clinical Decision Support in emergency medicine
Hashim Kareemi, Henry Li, Akshay Rajaram, et al.
Canadian Journal of Emergency Medicine (2025)
Closed Access | Times Cited: 1
Uncertainty of risk estimates from clinical prediction models: rationale, challenges, and approaches
Richard D. Riley, Gary S. Collins, Laura Kirton, et al.
BMJ (2025), pp. e080749-e080749
Closed Access | Times Cited: 1
Development and internal validation of a risk prediction model for dementia in a rural older population in China
Keke Liu, Tingting Hou, Yuqi Li, et al.
Alzheimer s & Dementia (2025) Vol. 21, Iss. 2
Open Access | Times Cited: 1
Opportunistic Screening of Chronic Liver Disease with Deep-Learning–Enhanced Echocardiography
Yuki Sahashi, Milos Vukadinovic, Fatemeh Amrollahi, et al.
NEJM AI (2025) Vol. 2, Iss. 3
Closed Access | Times Cited: 1
Artificial intelligence in clinical medicine: a state-of-the-art overview of systematic reviews with methodological recommendations for improved reporting
Giovanni Morone, Luigi De Angelis, Alex Martino Cinnera, et al.
Frontiers in Digital Health (2025) Vol. 7
Open Access | Times Cited: 1
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
Burak Koçak, Andrea Ponsiglione, Arnaldo Stanzione, et al.
Diagnostic and Interventional Radiology (2024)
Open Access | Times Cited: 11
Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection
Kim Robin van Daalen, Dudan Zhang, Stephen Kaptoge, et al.
The Lancet Global Health (2024) Vol. 12, Iss. 8, pp. e1343-e1358
Open Access | Times Cited: 8
ACcurate COnsensus Reporting Document (ACCORD) explanation and elaboration: Guidance and examples to support reporting consensus methods
Patrícia Logullo, Esther J van Zuuren, Christopher Winchester, et al.
PLoS Medicine (2024) Vol. 21, Iss. 5, pp. e1004390-e1004390
Open Access | Times Cited: 7
Prediction of incident atrial fibrillation using deep learning, clinical models and polygenic scores
Gilbert Jabbour, Alexis Nolin-Lapalme, Olivier Tastet, et al.
European Heart Journal (2024) Vol. 45, Iss. 46, pp. 4920-4934
Open Access | Times Cited: 6
Artificial Intelligence–Enhanced Risk Stratification of Cancer Therapeutics–Related Cardiac Dysfunction Using Electrocardiographic Images
Evangelos K. Oikonomou, Veer Sangha, Lovedeep Singh Dhingra, et al.
Circulation Cardiovascular Quality and Outcomes (2024) Vol. 18, Iss. 1
Closed Access | Times Cited: 6
Circulating Tumor Cell Count and Overall Survival in Patients With Metastatic Hormone-Sensitive Prostate Cancer
Amir Goldkorn, Catherine M. Tangen, Melissa Plets, et al.
JAMA Network Open (2024) Vol. 7, Iss. 10, pp. e2437871-e2437871
Open Access | Times Cited: 6
Data set terminology of deep learning in medicine: a historical review and recommendation
Shannon L. Walston, Hiroshi Seki, Hirotaka Takita, et al.
Japanese Journal of Radiology (2024) Vol. 42, Iss. 10, pp. 1100-1109
Closed Access | Times Cited: 5
Reporting Guidelines for Artificial Intelligence Studies in Healthcare (for Both Conventional and Large Language Models): What’s New in 2024
Seong Ho Park, Chong Hyun Suh
Korean Journal of Radiology (2024) Vol. 25, Iss. 8, pp. 687-687
Open Access | Times Cited: 5
Reflections on 2024 and Perspectives for 2025 for KJR
Seong Ho Park
Korean Journal of Radiology (2025) Vol. 26, Iss. 1, pp. 1-1
Closed Access
Page 1 - Next Page

Scroll to top