AIMC Topic: Adult

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Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms th...

Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation.

Radiology
Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive pulmonary disease (COPD). Conventional noncontrast CT provides airway and parenchymal measurements but cannot be used to directly determine lung funct...

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.

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...

Applying Machine Learning Techniques in Nomogram Prediction and Analysis for SMILE Treatment.

American journal of ophthalmology
PURPOSE: To analyze the outcome of machine learning technique for prediction of small incision lenticule extraction (SMILE) nomogram.

Accurate and robust segmentation of neuroanatomy in T1-weighted MRI by combining spatial priors with deep convolutional neural networks.

Human brain mapping
Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for quantitative volume, thickness, and shape measurements, as well as an important intermediate step in many preprocessing pipelines. This work introduce...

Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data.

The Lancet. Digital health
BACKGROUND: Cardiovascular outcomes for people with familial hypercholesterolaemia can be improved with diagnosis and medical management. However, 90% of individuals with familial hypercholesterolaemia remain undiagnosed in the USA. We aimed to accel...

Deep learning in the detection of high-grade glioma recurrence using multiple MRI sequences: A pilot study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
The identification of high-grade glioma (HGG) progression may pose a diagnostic dilemma due to similar appearances of treatment-related changes (TRC) (e.g. pseudoprogression or radionecrosis). Deep learning (DL) may be able to assist with this task. ...