AIMC Topic: Male

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Machine learning-aided personalized DTI tractographic planning for deep brain stimulation of the superolateral medial forebrain bundle using HAMLET.

Acta neurochirurgica
BACKGROUND: Growing interest exists for superolateral medial forebrain bundle (slMFB) deep brain stimulation (DBS) in psychiatric disorders. The surgical approach warrants tractographic rendition. Commercial stereotactic planning systems use determin...

Ensemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRI.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Accurate automated infarct segmentation is needed for acute ischemic stroke studies relying on infarct volumes as an imaging phenotype or biomarker that require large numbers of subjects. This study investigated whether an ens...

Quantifying ultrasonic mouse vocalizations using acoustic analysis in a supervised statistical machine learning framework.

Scientific reports
Examination of rodent vocalizations in experimental conditions can yield valuable insights into how disease manifests and progresses over time. It can also be used as an index of social interest, motivation, emotional development or motor function de...

Ultrasound prostate segmentation based on multidirectional deeply supervised V-Net.

Medical physics
PURPOSE: Transrectal ultrasound (TRUS) is a versatile and real-time imaging modality that is commonly used in image-guided prostate cancer interventions (e.g., biopsy and brachytherapy). Accurate segmentation of the prostate is key to biopsy needle p...

Reduction of operator radiation exposure using a passive robotic device during fluoroscopy-guided arterial puncture: an experimental study in a swine model.

European radiology experimental
BACKGROUND: Vascular interventions imply radiation exposure to the operating physician (OP). To reduce radiation exposure, we propose a novel passive robotic device for fluoroscopy-guided arterial puncturing.

Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning.

Scientific reports
Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial i...

Salivary microRNAs identified by small RNA sequencing and machine learning as potential biomarkers of alcohol dependence.

Epigenomics
Salivary miRNA can be easily accessible biomarkers of alcohol dependence (AD). The miRNA transcriptome in the saliva of 56 African-Americans (AAs; 28 AD patients/28 controls) and 64 European-Americans (EAs; 32 AD patients/32 controls) was profiled ...

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

Journal of affective disorders
BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS) treatment is an important purpose that eliminates financial and psychological consequences of applying inefficient therapy. To achieve this goal we p...

Deep Learning Convolutional Neural Networks for the Automatic Quantification of Muscle Fat Infiltration Following Whiplash Injury.

Scientific reports
Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated st...