AIMC Topic: Disease Progression

Clear Filters Showing 401 to 410 of 783 articles

Image-based consensus molecular subtype (imCMS) classification of colorectal cancer using deep learning.

Gut Jul 20, 2020
OBJECTIVE: Complex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), hi...
Biopsy RNA Datasets as Topic Deep Learning Consensus Gene Expression Regulation, Neoplastic Predictive Value of Tests Neoplasm Grading Humans Phenotype Prognosis Colorectal Neoplasms Biomarkers, Tumor Disease Progression Gene Expression Profiling
View on PubMed DOI

From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans.

European radiology Jul 18, 2020
OBJECTIVE: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression of COVID-19 using thick-section chest CT images.
Humans Artificial Intelligence SARS-CoV-2 Male Middle Aged Disease Progression Lung Pandemics COVID-19 Retrospective Studies Tomography, X-Ray Computed Female Coronavirus Infections Deep Learning Community-Acquired Infections China Betacoronavirus ROC Curve Pneumonia, Viral Pneumonia
View on PubMed DOI

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Aging Jul 9, 2020
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathoge...
Bayes Theorem Brain Female Humans Amyloid beta-Peptides Aged Alzheimer Disease Aged, 80 and over Disease Progression Image Interpretation, Computer-Assisted Male Longitudinal Studies Atrophy Magnetic Resonance Imaging Cluster Analysis Unsupervised Machine Learning
View on PubMed DOI

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Scientific reports Jul 3, 2020
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...
Humans Databases, Factual Brain Computer Simulation Disease Progression Parkinson Disease Models, Statistical Bayes Theorem Translational Research, Biomedical Alzheimer Disease Deep Learning User-Computer Interface Cohort Studies Polymorphism, Single Nucleotide Longitudinal Studies
View on PubMed DOI

Age-related Macular Degeneration: Nutrition, Genes and Deep Learning-The LXXVI Edward Jackson Memorial Lecture.

American journal of ophthalmology Jun 20, 2020
PURPOSE: To evaluate the importance of nutritional supplements, dietary pattern, and genetic associations in age-related macular degeneration (AMD); and to discuss the technique of artificial intelligence/deep learning to potentially enhance research...
Humans Disease Progression Deep Learning Dietary Supplements Visual Acuity Genetic Testing Macular Degeneration
View on PubMed DOI

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches.

Scientific reports Jun 19, 2020
OBJECTIVE: The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) approaches to predict serum levels of some adipokines/related inflammatory factors and their ratios ...
Adipose Tissue Knee Joint Adipokines Osteoarthritis, Knee Male Middle Aged Disease Progression Magnetic Resonance Imaging Humans Machine Learning Female Reproducibility of Results Aged
View on PubMed DOI

Machine Learning of 12-Lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients With Differential Outcomes.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Cardiac resynchronization therapy (CRT) improves heart failure outcomes but has significant nonresponse rates, highlighting limitations in ECG selection criteria: QRS duration (QRSd) ≥150 ms and subjective labeling of left bundle branch b...
Retrospective Studies Female Risk Factors Aged Male Ventricular Function, Left Stroke Volume Middle Aged Risk Assessment Disease Progression Humans Heart-Assist Devices Recovery of Function Heart Transplantation Predictive Value of Tests Bundle-Branch Block Signal Processing, Computer-Assisted Heart Failure Diagnosis, Computer-Assisted Cardiac Resynchronization Therapy Time Factors Electrocardiography Treatment Outcome Unsupervised Machine Learning
View on PubMed DOI

Artificial intelligence for interpretation of segments of whole body MRI in CNO: pilot study comparing radiologists versus machine learning algorithm.

Pediatric rheumatology online journal Jun 9, 2020
BACKGROUND: To initiate the development of a machine learning algorithm capable of comparing segments of pre and post pamidronate whole body MRI scans to assess treatment response and to compare the results of this algorithm with the analysis of a pa...
Whole Body Imaging Osteitis Pamidronate Radiologists Image Interpretation, Computer-Assisted Tibia Bone Density Conservation Agents Femur Treatment Outcome Support Vector Machine Magnetic Resonance Imaging Chronic Disease Humans Artificial Intelligence Machine Learning Sensitivity and Specificity Disease Progression Pilot Projects Adolescent
View on PubMed DOI

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one Jun 5, 2020
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...
Models, Biological Humans Datasets as Topic Machine Learning Renal Replacement Therapy Time-to-Treatment Retrospective Studies Time Factors Clinical Decision-Making ROC Curve Disease Progression Renal Insufficiency, Chronic Comorbidity Taiwan Severity of Illness Index
View on PubMed DOI

AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

NeuroImage. Clinical Jun 1, 2020
The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have...
Pattern Recognition, Automated Cognitive Dysfunction Humans Neuroimaging Age Factors Neural Networks, Computer Predictive Value of Tests Brain Alzheimer Disease Disease Progression Image Interpretation, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals