Articles with public access mandates - Andrew L. BeamLearn more
Not available anywhere: 2
Performance of a large language model on practice questions for the neonatal board examination
K Beam, P Sharma, B Kumar, C Wang, D Brodsky, CR Martin, A Beam
JAMA pediatrics 177 (9), 977-979, 2023
Mandates: US National Institutes of Health
National Needs Assessment of Utilization of Common Newborn Clinical Decision Support Tools
K Beam, C Wang, A Beam, R Clark, VN Tolia, KA Ahmad
American journal of perinatology, 2023
Mandates: US National Institutes of Health
Available somewhere: 49
Artificial intelligence in healthcare
KH Yu, AL Beam, IS Kohane
Nature biomedical engineering 2 (10), 719-731, 2018
Mandates: US National Institutes of Health
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
bmj 370, 2020
Mandates: US National Institutes of Health, UK Engineering and Physical Sciences …
Adversarial attacks on medical machine learning
SG Finlayson, JD Bowers, J Ito, JL Zittrain, AL Beam, IS Kohane
Science 363 (6433), 1287-1289, 2019
Mandates: US National Institutes of Health
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
S Cruz Rivera, X Liu, AW Chan, AK Denniston, MJ Calvert
Nature medicine 26 (9), 1351-1363, 2020
Mandates: US National Institutes of Health, UK Engineering and Physical Sciences …
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
Mandates: US National Institutes of Health
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial …
GS Collins, P Dhiman, CLA Navarro, J Ma, L Hooft, JB Reitsma, P Logullo, ...
BMJ open 11 (7), e048008, 2021
Mandates: Netherlands Organisation for Scientific Research, Cancer Research UK, UK …
A review of challenges and opportunities in machine learning for health
M Ghassemi, T Naumann, P Schulam, AL Beam, IY Chen, R Ranganath
AMIA Summits on Translational Science Proceedings 2020, 191, 2020
Mandates: US National Institutes of Health, Natural Sciences and Engineering Research …
Second opinion needed: communicating uncertainty in medical machine learning
B Kompa, J Snoek, AL Beam
npj Digital Medicine 4 (1), 1-6, 2021
Mandates: US National Institutes of Health
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
Mandates: US National Science Foundation, US National Institutes of Health, American …
Challenges to the reproducibility of machine learning models in health care
AL Beam, AK Manrai, M Ghassemi
Jama 323 (4), 305-306, 2020
Mandates: US National Institutes of Health
Clinical concept embeddings learned from massive sources of multimodal medical data
AL Beam, B Kompa, A Schmaltz, I Fried, G Weber, N Palmer, X Shi, T Cai, ...
Pacific Symposium on Biocomputing 2020, 295-306, 2019
Mandates: US National Institutes of Health
Time to reality check the promises of machine learning-powered precision medicine
J Wilkinson, KF Arnold, EJ Murray, M van Smeden, K Carr, R Sippy, ...
The Lancet Digital Health 2 (12), e677-e680, 2020
Mandates: US National Institutes of Health, Wellcome Trust, Federal Ministry of …
Estimates of healthcare spending for preterm and low-birthweight infants in a commercially insured population: 2008–2016
AL Beam, I Fried, N Palmer, D Agniel, G Brat, K Fox, I Kohane, A Sinaiko, ...
Journal of Perinatology 40 (7), 1091-1099, 2020
Mandates: US National Institutes of Health
Artificial intelligence in medicine
AL Beam, JM Drazen, IS Kohane, TY Leong, AK Manrai, EJ Rubin
New England Journal of Medicine 388 (13), 1220-1221, 2023
Mandates: US National Institutes of Health
Machine learning for patient risk stratification: standing on, or looking over, the shoulders of clinicians?
BK Beaulieu-Jones, W Yuan, GA Brat, AL Beam, G Weber, M Ruffin, ...
NPJ digital medicine 4 (1), 62, 2021
Mandates: US National Institutes of Health
Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction
ML Chen, A Doddi, J Royer, L Freschi, M Schito, M Ezewudo, IS Kohane, ...
EBioMedicine 43, 356-369, 2019
Mandates: Bill & Melinda Gates Foundation, US National Institutes of Health
Trends and focus of machine learning applications for health research
B Beaulieu-Jones, SG Finlayson, C Chivers, I Chen, M McDermott, ...
JAMA network open 2 (10), e1914051-e1914051, 2019
Mandates: US National Institutes of Health
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
Mandates: Netherlands Organisation for Scientific Research, Cancer Research UK, UK …
Publication and funding information is determined automatically by a computer program