AI in health and medicine
Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
Lung cancer LDCT screening and mortality reduction—evidence, pitfalls and future perspectives
In the past decade, the introduction of molecularly targeted agents and immune-checkpoint
inhibitors has led to improved survival outcomes for patients with advanced-stage lung …
inhibitors has led to improved survival outcomes for patients with advanced-stage lung …
Sybil: a validated deep learning model to predict future lung cancer risk from a single low-dose chest computed tomography
PURPOSE Low-dose computed tomography (LDCT) for lung cancer screening is effective,
although most eligible people are not being screened. Tools that provide personalized …
although most eligible people are not being screened. Tools that provide personalized …
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal …
Background Accurate prediction of tumour response to neoadjuvant chemoradiotherapy
enables personalised perioperative therapy for locally advanced rectal cancer. We aimed to …
enables personalised perioperative therapy for locally advanced rectal cancer. We aimed to …
[HTML][HTML] CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients
Rationale: Some patients with coronavirus disease 2019 (COVID-19) rapidly develop
respiratory failure or even die, underscoring the need for early identification of patients at …
respiratory failure or even die, underscoring the need for early identification of patients at …
Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment
C Zhang, J Xu, R Tang, J Yang, W Wang, X Yu… - Journal of Hematology & …, 2023 - Springer
Research into the potential benefits of artificial intelligence for comprehending the intricate
biology of cancer has grown as a result of the widespread use of deep learning and …
biology of cancer has grown as a result of the widespread use of deep learning and …
Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study
Background Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple
heart abnormalities that covers a wide range of arrhythmias, with better-than-human …
heart abnormalities that covers a wide range of arrhythmias, with better-than-human …
Artificial intelligence: A critical review of applications for lung nodule and lung cancer
C de Margerie-Mellon, G Chassagnon - Diagnostic and Interventional …, 2023 - Elsevier
Artificial intelligence (AI) is a broad concept that usually refers to computer programs that
can learn from data and perform certain specific tasks. In the recent years, the growth of …
can learn from data and perform certain specific tasks. In the recent years, the growth of …
Assessing the accuracy of a deep learning method to risk stratify indeterminate pulmonary nodules
Rationale: The management of indeterminate pulmonary nodules (IPNs) remains
challenging, resulting in invasive procedures and delays in diagnosis and treatment …
challenging, resulting in invasive procedures and delays in diagnosis and treatment …