AIMC Topic: Disease Progression
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Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability.
Journal of imaging informatics in medicine
Jun 13, 2024
The majority of deep learning models in medical image analysis concentrate on single snapshot timepoint circumstances, such as the identification of current pathology on a given image or volume. This is often in contrast to the diagnostic methodology...
Decoding temporal heterogeneity in NSCLC through machine learning and prognostic model construction.
World journal of surgical oncology
Jun 13, 2024
BACKGROUND: Non-small cell lung cancer (NSCLC) is a prevalent and heterogeneous disease with significant genomic variations between the early and advanced stages. The identification of key genes and pathways driving NSCLC tumor progression is critica...
Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis.
Neuroradiology
Jun 12, 2024
PURPOSE: Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, rad...
Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.
Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
Jun 8, 2024
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...
Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model.
Journal of vascular surgery
Jun 6, 2024
BACKGROUND: Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Soci...
Humans
Retrospective Studies
Aortography
Imaging, Three-Dimensional
Predictive Value of Tests
Acute Disease
Radiographic Image Interpretation, Computer-Assisted
Aortic Aneurysm, Thoracic
Computed Tomography Angiography
Automation
Aortic Aneurysm
Middle Aged
Aortic Dissection
Female
Disease Progression
Reproducibility of Results
Deep Learning
Aged
Time Factors
Male
First experiences with machine learning predictions of accelerated declining eGFR slope of living kidney donors 3 years after donation.
Journal of nephrology
Jun 5, 2024
BACKGROUND: Living kidney donors are screened pre-donation to estimate the risk of end-stage kidney disease (ESKD). We evaluate Machine Learning (ML) to predict the progression of kidney function deterioration over time using the estimated GFR (eGFR)...
Machine Learning Identifies Key Proteins in Primary Sclerosing Cholangitis Progression and Links High CCL24 to Cirrhosis.
International journal of molecular sciences
May 30, 2024
Primary sclerosing cholangitis (PSC) is a rare, progressive disease, characterized by inflammation and fibrosis of the bile ducts, lacking reliable prognostic biomarkers for disease activity. Machine learning applied to broad proteomic profiling of s...
A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.
Scientific reports
May 29, 2024
Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annual...
Machine learning for prediction of chronic kidney disease progression: Validation of the Klinrisk model in the CANVAS Program and CREDENCE trial.
Diabetes, obesity & metabolism
May 28, 2024
AIM: To validate the Klinrisk machine learning model for prediction of chronic kidney disease (CKD) progression in patients with type 2 diabetes in the pooled CANVAS/CREDENCE trials.
Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression.
NeuroImage. Clinical
May 26, 2024
Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multipl...
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