AIMC Topic: Adult

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Impact of the rise of artificial intelligence in radiology: What do radiologists think?

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the perception, knowledge, wishes and expectations of a sample of French radiologists towards the rise of artificial intelligence (AI) in radiology.

Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques.

PloS one
OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the ...

Development of a machine learning algorithm for prediction of failure of nonoperative management in spinal epidural abscess.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Data regarding risk of failure of nonoperative management in spinal epidural abscess (SEA) are limited. Given the potential for deterioration with treatment failure, a tool that predicts the probability of failure would be of grea...

Adaptive neural network classifier for decoding MEG signals.

NeuroImage
We introduce two Convolutional Neural Network (CNN) classifiers optimized for inferring brain states from magnetoencephalographic (MEG) measurements. Network design follows a generative model of the electromagnetic (EEG and MEG) brain signals allowin...

Can machine learning predict resecability of a peritoneal carcinomatosis?

Surgical oncology
BACKGROUND: Approximately 20% of initially eligible patients in a HIPEC procedure eventually underwent a simple surgical exploration. These procedures are called 'open & close' (O & C) representing up to 48% of surgery. The objective of this study wa...

Spatiotemporal gait characteristic changes with gait training using the hybrid assistive limb for chronic stroke patients.

Gait & posture
BACKGROUND: Robotic rehabilitation has been attracting attention as a means to carry out "intensive", "repetitive", "task-specific", gait training. The newly developed robotic device, the Hybrid Assistive Limb (HAL), is thought to have the possibilit...

Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis.

JAMA network open
IMPORTANCE: Assessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clinical practice is limited by the requirement for experienced human reviewers.

Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.

JAMA network open
IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many patients do not respond to biological monotherapy. Identification of likely responders could reduce costs and delays in remission.

Machine-learned target volume delineation of F-FDG PET images after one cycle of induction chemotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Biological tumour volume (GTV) delineation on F-FDG PET acquired during induction chemotherapy (ICT) is challenging due to the reduced metabolic uptake and volume of the GTV. Automatic segmentation algorithms applied to F-FDG PET (PET-AS) imaging hav...

Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using support vector machine.

EBioMedicine
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is a devastating disease with high mortality rate. This study aimed to predict hematoma expansion in spontaneous ICH from routinely available variables by using support vector machine (SVM) metho...