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 …
[HTML][HTML] Deep learning for chest X-ray analysis: A survey
Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …
image analysis tasks. As the most commonly performed radiological exam, chest …
External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
Key challenges for delivering clinical impact with artificial intelligence
Background Artificial intelligence (AI) research in healthcare is accelerating rapidly, with
potential applications being demonstrated across various domains of medicine. However …
potential applications being demonstrated across various domains of medicine. However …
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
High-performance medicine: the convergence of human and artificial intelligence
EJ Topol - Nature medicine, 2019 - nature.com
The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …
enabled by the use of labeled big data, along with markedly enhanced computing power …
Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study
Background Chest x-rays are widely used in clinical practice; however, interpretation can be
hindered by human error and a lack of experienced thoracic radiologists. Deep learning has …
hindered by human error and a lack of experienced thoracic radiologists. Deep learning has …
Leveraging data science to combat COVID-19: A comprehensive review
COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a
pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020 …
pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020 …
Challenges and opportunities beyond structured data in analysis of electronic health records
M Tayefi, P Ngo, T Chomutare… - Wiley …, 2021 - Wiley Online Library
Electronic health records (EHR) contain a lot of valuable information about individual
patients and the whole population. Besides structured data, unstructured data in EHRs can …
patients and the whole population. Besides structured data, unstructured data in EHRs can …
Association of artificial intelligence–aided chest radiograph interpretation with reader performance and efficiency
Importance The efficient and accurate interpretation of radiologic images is paramount.
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …
Objective To evaluate whether a deep learning–based artificial intelligence (AI) engine used …