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 …
[HTML][HTML] Deep learning in medical imaging
The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by
the human brain system, was developed by connecting layers with artificial neurons …
the human brain system, was developed by connecting layers with artificial neurons …
Machine learning approach to identify stroke within 4.5 hours
H Lee, EJ Lee, S Ham, HB Lee, JS Lee, SU Kwon… - Stroke, 2020 - Am Heart Assoc
Background and Purpose—We aimed to investigate the ability of machine learning (ML)
techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion …
techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion …
Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma
Y Hu, C ** review
Although individually rare, collectively more than 7,000 rare diseases affect about 10% of
patients. Each of the rare diseases impacts the quality of life for patients and their families …
patients. Each of the rare diseases impacts the quality of life for patients and their families …
Pile: Robust privacy-preserving federated learning via verifiable perturbations
Federated learning (FL) protects training data in clients by collaboratively training local
machine learning models of clients for a global model, instead of directly feeding the training …
machine learning models of clients for a global model, instead of directly feeding the training …
Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status
We investigated the ability of machine-learning classifiers on radiomics from pre-treatment
multiparametric magnetic resonance imaging (MRI) to accurately predict human …
multiparametric magnetic resonance imaging (MRI) to accurately predict human …