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Predictors for trifecta achievement of robot-assisted partial nephrectomy in high-complexity tumors (Preoperative Aspects and Dimensions Used for an Anatomical score ≥10).

Asian journal of endoscopic surgery
INTRODUCTION: Robot-assisted partial nephrectomy (RAPN) is emerging as an effective treatment oncologically and functionally for clinically localized renal tumors. However, RAPN in high-complexity tumors with a Preoperative Aspects and Dimensions Use...

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API), based on digital subtraction angiography (DSA), is a quantitative imaging tool that may be used to extract contrast flow parameters related to hemodynamic conditions in abnormal pathologies such as i...

Pharmacokinetic-pharmacodynamic assessment of the ivermectin and abamectin nematodicidal interaction in cattle.

Veterinary parasitology
In a context of nematodicidal resistance, anthelmintic combinations have emerged as a reliable pharmacological strategy to control gastrointestinal nematodes in grazing systems of livestock production. The current work evaluated the potential drug-dr...

Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.

NeuroImage
Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional meas...

Accurate Ambulatory Gait Analysis in Walking and Running Using Machine Learning Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Wearable sensors have been proposed as alternatives to traditional laboratory equipment for low-cost and portable real-time gait analysis in unconstrained environments. However, the moderate accuracy of these systems currently limits their widespread...

Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease.

Computer methods and programs in biomedicine
OBJECTIVES: Identifying acute exacerbations in chronic obstructive pulmonary disease (AECOPDs) is of utmost importance for reducing the associated mortality and financial burden. In this research, the authors aimed to develop identification models fo...

Decoding and mapping task states of the human brain via deep learning.

Human brain mapping
Support vector machine (SVM)-based multivariate pattern analysis (MVPA) has delivered promising performance in decoding specific task states based on functional magnetic resonance imaging (fMRI) of the human brain. Conventionally, the SVM-MVPA requir...

Deep learning segmentation of orbital fat to calibrate conventional MRI for longitudinal studies.

NeuroImage
In conventional non-quantitative magnetic resonance imaging, image contrast is consistent within images, but absolute intensity can vary arbitrarily between scans. For quantitative analysis of intensity data, images are typically normalized to a cons...