AIMC Topic: Aged, 80 and over

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Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Nature communications
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...

Application of deep learning to understand resilience to Alzheimer's disease pathology.

Brain pathology (Zurich, Switzerland)
People who have Alzheimer's disease neuropathologic change (ADNC) typically associated with dementia but not the associated cognitive decline can be considered to be "resilient" to the effects of ADNC. We have previously reported lower neocortical le...

Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.

Japanese journal of radiology
PURPOSE: To evaluate whether early chest computed tomography (CT) lesions quantified by an artificial intelligence (AI)-based commercial software and blood test values at the initial presentation can differentiate the severity of COVID-19 pneumonia.

Deep recurrent model for individualized prediction of Alzheimer's disease progression.

NeuroImage
Alzheimer's disease (AD) is known as one of the major causes of dementia and is characterized by slow progression over several years, with no treatments or available medicines. In this regard, there have been efforts to identify the risk of developin...

Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.

Clinical radiology
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...

Deep Learning Model for Automated Detection and Classification of Central Canal, Lateral Recess, and Neural Foraminal Stenosis at Lumbar Spine MRI.

Radiology
Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve -productivity and the consistency of reporting. Purpose To develop a DL model for automated detection and classification of lumb...

Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

Cancer medicine
BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning m...