AIMC Topic: Retrospective Studies

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Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.

F1000Research
A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients.  Several kidney graft outcome prediction models, developed using machine learning methods, are...

Impact of age at onset on the phenomenology of depression in treatment-seeking adults in the STAR*D trial.

Journal of affective disorders
BACKGROUND: - Adolescence is characterized by biological, emotional, and behavioral changes. The onset of depression during this vulnerable time may confer specific risks. This study examined whether symptoms of depression were associated with age at...

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images.

European radiology experimental
BACKGROUND: Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a con...

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department.

Radiology
BackgroundThe performance of a deep learning (DL) algorithm should be validated in actual clinical situations, before its clinical implementation.PurposeTo evaluate the performance of a DL algorithm for identifying chest radiographs with clinically r...

SVM recursive feature elimination analyses of structural brain MRI predicts near-term relapses in patients with clinically isolated syndromes suggestive of multiple sclerosis.

NeuroImage. Clinical
Machine learning classification is an attractive approach to automatically differentiate patients from healthy subjects, and to predict future disease outcomes. A clinically isolated syndrome (CIS) is often the first presentation of multiple sclerosi...

Is obesity a contraindication for kidney donation?

Surgical endoscopy
INTRODUCTION: To enlarge the donor pool, kidney donors with obesity have been considered. We hypothesized that it is safe for patients with obesity to serve as living kidney donors.

Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.

Clinical lung cancer
INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced non-small-cell lung cancer (NSCLC). However, radiation-induced cardiac toxicity among patients with ea...

Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural netwo...

Deep-Learning-Based Neural Tissue Segmentation of MRI in Multiple Sclerosis: Effect of Training Set Size.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The dependence of deep-learning (DL)-based segmentation accuracy of brain MRI on the training size is not known.

A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.

Scandinavian cardiovascular journal : SCJ
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...