Lauren Oakden-Rayner

Citée par

	Toutes	Depuis 2020
Citations	6994	6783
indice h	30	29
indice i10	48	47

2400

1200

600

1800

20172018201920202021202220232024202518 57 112 268 652 1182 1825 2399 410

Accès public

Tout afficher

18 articles

0 article

disponibles

non disponibles

Sur la base des exigences liées au financement

Coauteurs

Lyle John PalmerProfessor of Genetic Epidemiology, Adelaide UniversityAdresse e-mail validée de adelaide.edu.au
Dr. Marzyeh GhassemiAssociate Professor, EECS/IMES, MITAdresse e-mail validée de mit.edu
Gustavo CarneiroProfessor of AI and Machine Learning, University of SurreyAdresse e-mail validée de surrey.ac.uk
Xiao LiuUniversity Hospitals Birmingham, University of Birmingham, UKAdresse e-mail validée de bham.ac.uk
Stephen BacchiMassachusetts General HospitalAdresse e-mail validée de mgh.harvard.edu
Alastair DennistonConsultant Ophthalmologist/Hon Professor, University Hospitals Birmingham/University of BirminghamAdresse e-mail validée de bham.ac.uk
William GaleMicrosoftAdresse e-mail validée de microsoft.com
Andrew P. BradleyWhipbird SignalsAdresse e-mail validée de ieee.org
Andrew L. BeamCTO FL97, Inc. | Associate Professor, Harvard UniversityAdresse e-mail validée de hms.harvard.edu
Jacinto C. NascimentoInstitute for Systems and Robotics (ISR/IST), LARSyS, Instituto Superior TécnicoAdresse e-mail validée de isr.ist.utl.pt
Melanie CalvertUniversity of BirminghamAdresse e-mail validée de bham.ac.uk
Jared DunnmonStanford UniversityAdresse e-mail validée de stanford.edu
Christopher RéComputer Science, Stanford UniversityAdresse e-mail validée de cs.stanford.edu
John ZechNew York Presbyterian - ColumbiaAdresse e-mail validée de columbia.edu
Amali WeerasingheUniversity of AdelaideAdresse e-mail validée de adelaide.edu.au
Samuel G. FinlaysonMD-PhD. Pediatrics-Genetics Resident at UW/Seattle Children'sAdresse e-mail validée de seattlechildrens.org
Samantha Cruz RiveraResearch Fellow, University of BirminghamAdresse e-mail validée de bham.ac.uk

Suivre

Lauren Oakden-Rayner

Autres nomsLuke Oakden-Rayner

Australian Institute for Machine Learning. University of Adelaide. Royal Adelaide Hospital.

Adresse e-mail validée de adelaide.edu.au - Page d'accueil

Radiology Image Analysis Machine Learning Deep Learning Medical Informatics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension X Liu, SC Rivera, D Moher, MJ Calvert, AK Denniston, H Ashrafian, ... The Lancet Digital Health 2 (10), e537-e548, 2020	958	2020
The false hope of current approaches to explainable artificial intelligence in health care M Ghassemi, L Oakden-Rayner, AL Beam The Lancet Digital Health 3 (11), e745-e750, 2021	893	2021
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension SC Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert, H Ashrafian, ... The Lancet Digital Health 2 (10), e549-e560, 2020	772	2020
AI recognition of patient race in medical imaging: a modelling study JW Gichoya, I Banerjee, AR Bhimireddy, JL Burns, LA Celi, LC Chen, ... The Lancet Digital Health 4 (6), e406-e414, 2022	424	2022
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging L Oakden-Rayner, J Dunnmon, G Carneiro, C Ré Proceedings of the ACM conference on health, inference, and learning, 151-159, 2020	423	2020
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... bmj 377, 2022	407	2022
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods GS Collins, KGM Moons, P Dhiman, RD Riley, AL Beam, B Van Calster, ... bmj 385, 2024	327	2024
Deep learning predicts hip fracture using confounding patient and healthcare variables MA Badgeley, JR Zech, L Oakden-Rayner, BS Glicksberg, M Liu, W Gale, ... NPJ digital medicine 2 (1), 31, 2019	236	2019
Exploring large-scale public medical image datasets L Oakden-Rayner Academic radiology 27 (1), 106-112, 2020	199	2020
Precision radiology: predicting longevity using feature engineering and deep learning methods in a radiomics framework L Oakden-Rayner, G Carneiro, T Bessen, JC Nascimento, AP Bradley, ... Scientific reports 7 (1), 1648, 2017	185	2017
A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology J Scheetz, P Rothschild, M McGuinness, X Hadoux, HP Soyer, M Janda, ... Scientific reports 11 (1), 5193, 2021	184	2021
The medical algorithmic audit X Liu, B Glocker, MM McCradden, M Ghassemi, AK Denniston, ... The Lancet Digital Health 4 (5), e384-e397, 2022	181	2022
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study JCY Seah, CHM Tang, QD Buchlak, XG Holt, JB Wardman, A Aimoldin, ... The Lancet Digital Health 3 (8), e496-e506, 2021	177	2021
Detecting hip fractures with radiologist-level performance using deep neural networks W Gale, L Oakden-Rayner, G Carneiro, AP Bradley, LJ Palmer arXiv preprint arXiv:1711.06504, 2017	134	2017
Deep learning in the prediction of ischaemic stroke thrombolysis functional outcomes: a pilot study S Bacchi, T Zerner, L Oakden-Rayner, T Kleinig, S Patel, J Jannes Academic radiology 27 (2), e19-e23, 2020	118	2020
The value of standards for health datasets in artificial intelligence-based applications A Arora, JE Alderman, J Palmer, S Ganapathi, E Laws, MD Mccradden, ... Nature Medicine 29 (11), 2929-2938, 2023	107	2023
Producing radiologist-quality reports for interpretable deep learning W Gale, L Oakden-Rayner, G Carneiro, LJ Palmer, AP Bradley 2019 IEEE 16th international symposium on biomedical imaging (ISBI 2019 …, 2019	102*	2019
Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA AP Brady, B Allen, J Chong, E Kotter, N Kottler, J Mongan, ... Canadian Association of Radiologists Journal 75 (2), 226-244, 2024	94	2024
Machine learning in the prediction of medical inpatient length of stay S Bacchi, Y Tan, L Oakden‐Rayner, J Jannes, T Kleinig, S Koblar Internal medicine journal 52 (2), 176-185, 2022	87	2022
Reading race: AI recognises patient's racial identity in medical images I Banerjee, AR Bhimireddy, JL Burns, LA Celi, LC Chen, R Correa, ... arXiv preprint arXiv:2107.10356, 2021	82	2021

Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.

Articles 1–20

Nombre de citations par an

Citations en double

Citations fusionnées

Ajouter les coauteursCoauteurs

Suivre

Citée par

Coauteurs