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Where medical statistics meets artificial intelligence
Where Medical Statistics Meets Artificial Intelligence | New England Journal of Medicine Skip to
main content The New England Journal of Medicine homepage Advanced Search SEARCH …
main content The New England Journal of Medicine homepage Advanced Search SEARCH …
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
A growing number of artificial intelligence (AI)-based clinical decision support systems are
showing promising performance in preclinical, in silico, evaluation, but few have yet …
showing promising performance in preclinical, in silico, evaluation, but few have yet …
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 …
Introduction The Transparent Reporting of a multivariable prediction model of Individual
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …
AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …
Artificial intelligence in fracture detection: a systematic review and meta-analysis
Background Patients with fractures are a common emergency presentation and may be
misdiagnosed at radiologic imaging. An increasing number of studies apply artificial …
misdiagnosed at radiologic imaging. An increasing number of studies apply artificial …
[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …
reporting by providing evidence-based recommendations for the minimum set of items to be …
Deep learning for caries detection: a systematic review
Objectives Detecting caries lesions is challenging for dentists, and deep learning models
may help practitioners to increase accuracy and reliability. We aimed to systematically …
may help practitioners to increase accuracy and reliability. We aimed to systematically …
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
Skin cancers occur commonly worldwide. The prognosis and disease burden are highly
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …
dependent on the cancer type and disease stage at diagnosis. We systematically reviewed …