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Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions.

Annals of clinical and translational neurology
OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterog...

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography.

European radiology experimental
BACKGROUND: Automatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technical parameters and the presence...

Machine learning identifies the dynamics and influencing factors in an auditory category learning experiment.

Scientific reports
Human learning is one of the main topics in psychology and cognitive neuroscience. The analysis of experimental data, e.g. from category learning experiments, is a major challenge due to confounding factors related to perceptual processing, feedback ...

Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.

Human brain mapping
Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathology. Here, we applied a novel supervised machine learning method, combining the strengths of a priori theoretical insights with a data-driven approach...

Predicting in-hospital mortality of patients with febrile neutropenia using machine learning models.

International journal of medical informatics
BACKGROUND: Febrile neutropenia (FN) has been associated with high mortality among adults with cancer. Current systems for early detection of inpatient FN mortality are based on scoring indexes that require intensive physicians' subjective evaluation...

Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis.

PloS one
Assessing the well-being of an animal is hindered by the limitations of efficient communication between humans and animals. Instead of direct communication, a variety of parameters are employed to evaluate the well-being of an animal. Especially in t...

Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.

AJR. American journal of roentgenology
The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. Retrospective review (April-May 2019) of the cases of adults...