AIMC Topic: Predictive Value of Tests
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Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans.
Scientific reports
Jan 7, 2022
Diabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin in pancreas that results in high glucose level in blood. The disease is also associated with other c...
Contactless facial video recording with deep learning models for the detection of atrial fibrillation.
Scientific reports
Jan 7, 2022
Atrial fibrillation (AF) is often asymptomatic and paroxysmal. Screening and monitoring are needed especially for people at high risk. This study sought to use camera-based remote photoplethysmography (rPPG) with a deep convolutional neural network (...
Reproducibility of Results
Aged
Aged, 80 and over
Male
Middle Aged
Humans
Prospective Studies
Female
Regional Blood Flow
Atrial Fibrillation
Heart Rate
Video Recording
Face
Diagnosis, Computer-Assisted
Pulsatile Flow
Deep Learning
Time Factors
Image Processing, Computer-Assisted
Photoplethysmography
Electrocardiography
Predictive Value of Tests
Skin
Accelerated cardiac T mapping in four heartbeats with inline MyoMapNet: a deep learning-based T estimation approach.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Jan 6, 2022
PURPOSE: To develop and evaluate MyoMapNet, a rapid myocardial T mapping approach that uses fully connected neural networks (FCNN) to estimate T values from four T-weighted images collected after a single inversion pulse in four heartbeats (Look-Lock...
Postoperative delirium prediction using machine learning models and preoperative electronic health record data.
BMC anesthesiology
Jan 3, 2022
BACKGROUND: Accurate, pragmatic risk stratification for postoperative delirium (POD) is necessary to target preventative resources toward high-risk patients. Machine learning (ML) offers a novel approach to leveraging electronic health record (EHR) d...
Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.
The Journal of pathology
Dec 28, 2021
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...
Predictive Value of Tests
Neoplasm Staging
Biopsy
Microscopy
Lymph Nodes
Colorectal Neoplasms
Image Interpretation, Computer-Assisted
Lymphatic Metastasis
Risk Assessment
Proof of Concept Study
Early Detection of Cancer
Diagnosis, Computer-Assisted
Adipose Tissue
Humans
Retrospective Studies
Deep Learning
Reproducibility of Results
Risk Factors
Finite Element Assessment of Bone Fragility from Clinical Images.
Current osteoporosis reports
Dec 21, 2021
PURPOSE OF REVIEW: We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.
Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes.
Journal of cardiovascular computed tomography
Dec 17, 2021
BACKGROUND: Low-dose computed tomography (LDCT) are performed routinely for lung cancer screening. However, a large amount of nonpulmonary data from these scans remains unassessed. We aimed to validate a deep learning model to automatically segment a...
Incorporating artificial intelligence in urology: Supervised machine learning algorithms demonstrate comparative advantage over nomograms in predicting biochemical recurrence after prostatectomy.
The Prostate
Dec 2, 2021
OBJECTIVE: After radical prostatectomy (RP), one-third of patients will experience biochemical recurrence (BCR), which is associated with subsequent metastasis and cancer-specific mortality. We employed machine learning (ML) algorithms to predict BCR...
Humans
Artificial Intelligence
Computer Simulation
Prognosis
Reproducibility of Results
Algorithms
Biomarkers
Supervised Machine Learning
Neoplasm Metastasis
Prostatectomy
Regression Analysis
Male
Recurrence
Comparative Effectiveness Research
Predictive Value of Tests
Middle Aged
Prostatic Neoplasms
Risk Assessment
Neoplasm Staging
Nomograms
Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients.
JAMA network open
Dec 1, 2021
IMPORTANCE: Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice.
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