AIMC Topic: Male

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Computational modeling of the monoaminergic neurotransmitter and male neuroendocrine systems in an analysis of therapeutic neuroadaptation to chronic antidepressant.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Second-line depression treatment involves augmentation with one (rarely two) additional drugs, of chronic administration of a selective serotonin reuptake inhibitor (SSRI), which is the first-line depression treatment. Unfortunately, many depressed p...

Robot-assisted versus manual navigated stereoelectroencephalography in adult medically-refractory epilepsy patients.

Epilepsy research
OBJECTIVE: Stereoelectroencephalography (SEEG) has experienced a recent growth in adoption for epileptogenic zone (EZ) localization. Advances in robotics have the potential to improve the efficiency and safety of this intracranial seizure monitoring ...

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

Journal of applied clinical medical physics
PURPOSE: Knowledge-based planning (KBP) techniques have been reported to improve plan quality, efficiency, and consistency in radiation therapy. However, plan complexity and deliverability have not been addressed previously for treatment plans guided...

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Journal of medical systems
Few studies have addressed the predictive value of arterial stiffness determined by pulse wave velocity (PWV) in a high-risk population with no prevalent cardiovascular disease and with obesity, hypertension, hyperglycemia, and preserved kidney funct...

Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop a deep learning (DL) model for automated detection of glaucoma and to compare diagnostic capability against hand-craft features (HCFs) based on spectral domain optical coherence tomography (SD-OCT) peripapillary retinal nerve fibe...

Decoding rumination: A machine learning approach to a transdiagnostic sample of outpatients with anxiety, mood and psychotic disorders.

Journal of psychiatric research
OBJECTIVE: To employ machine learning algorithms to examine patterns of rumination from RDoC perspective and to determine which variables predict high levels of maladaptive rumination across a transdiagnostic sample.

Deep Learning for Automated Measurement of Hemorrhage and Perihematomal Edema in Supratentorial Intracerebral Hemorrhage.

Stroke
Background and Purpose- Volumes of hemorrhage and perihematomal edema (PHE) are well-established biomarkers of primary and secondary injury, respectively, in spontaneous intracerebral hemorrhage. An automated imaging pipeline capable of accurately an...

A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
To enhance the performance of the brain-actuated robot system, a novel shared controller based on Bayesian approach is proposed for intelligently combining robot automatic control and brain-actuated control, which takes into account the uncertainty o...

Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: Deep learning-based auto-segmented contours (DC) aim to alleviate labour intensive contouring of organs at risk (OAR) and clinical target volumes (CTV). Most previous DC validation studies have a limited number of expert observers for com...