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MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer.

Scientific reports
Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of patients with LARC shows a complete response...

Key factors in a rigorous longitudinal image-based assessment of retinopathy of prematurity.

Scientific reports
To describe a database of longitudinally graded telemedicine retinal images to be used as a comparator for future studies assessing grader recall bias and ability to detect typical progression (e.g. International Classification of Retinopathy of Prem...

Image-level supervised segmentation for human organs with confidence cues.

Physics in medicine and biology
Image segmentation for human organs is an important task for the diagnosis and treatment of diseases. Current deep learning-based methods are fully supervised and need pixel-level labels. Since the medical images are highly specialized and complex, t...

Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.

Parkinsonism & related disorders
INTRODUCTION: Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonanc...

Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units.

Sensors (Basel, Switzerland)
This paper develops Deep Neural Network (DNN) models that can recognize stroke gaits. Stroke patients usually suffer from partial disability and develop abnormal gaits that can vary widely and need targeted treatments. Evaluation of gait patterns is ...

Cardiac Operative Risk in Latin America: A Comparison of Machine Learning Models vs EuroSCORE-II.

The Annals of thoracic surgery
BACKGROUND: Machine learning is a useful tool for predicting medical outcomes. This study aimed to develop a machine learning-based preoperative score to predict cardiac surgical operative mortality.

TractLearn: A geodesic learning framework for quantitative analysis of brain bundles.

NeuroImage
Deep learning-based convolutional neural networks have recently proved their efficiency in providing fast segmentation of major brain fascicles structures, based on diffusion-weighted imaging. The quantitative analysis of brain fascicles then relies ...

A novel dataset and deep learning-based approach for marker-less motion capture during gait.

Gait & posture
BACKGROUND: The deep learning-based human pose estimation methods, which can estimate joint centers position, have achieved promising results on the publicly available human pose datasets (e.g., Human3.6 M). However, these datasets may be less effici...

Toward improving functional recovery in spinal cord injury using robotics: a pilot study focusing on ankle rehabilitation.

Expert review of medical devices
BACKGROUND: Conventional physical therapy interventions are strongly recommended to improve ambulation potential and upright mobility in persons with incomplete spinal cord injury (iSCI). Ankle rehabilitation plays a significant role, as it aims to s...