AIMC Topic: Female

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SurgAI: deep learning for computerized laparoscopic image understanding in gynaecology.

Surgical endoscopy
BACKGROUND: In laparoscopy, the digital camera offers surgeons the opportunity to receive support from image-guided surgery systems. Such systems require image understanding, the ability for a computer to understand what the laparoscope sees. Image u...

Acceleration of three-dimensional diffusion magnetic resonance imaging using a kernel low-rank compressed sensing method.

NeuroImage
Diffusion Magnetic Resonance Imaging (dMRI) has shown great potential in probing tissue microstructure and structural connectivity in the brain but is often limited by the lengthy scan time needed to sample the diffusion profile by acquiring multiple...

Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images.

Translational vision science & technology
PURPOSE: To develop and evaluate a deep learning (DL) system for retinal hemorrhage (RH) screening using ultra-widefield fundus (UWF) images.

Semantic and structural image segmentation for prosthetic vision.

PloS one
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

Journal of the Royal Society, Interface
The objective is to test automated estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimatio...

Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identi...

Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Pancreatic cancer remains a disease of high mortality despite advanced diagnostic techniques. Mucins (MUC) play crucial roles in carcinogenesis and tumor invasion in pancreatic cancers. MUC1 and MUC4 expression are related to the aggressive ...

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

Acta neurologica Belgica
The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on mobility, activities of daily living (ADLs), and quality of life (QoL) in stroke rehabilitation. Fifty-one stroke patients randomly assigned to Group 1...

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Radiology
Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial role in the treatment of patients with acute ischemic stroke (AIS). Patients with extensive infarction are unlikely to benefit from thrombolysis or t...

Machine Learning Approach to Identify Stroke Within 4.5 Hours.

Stroke
Background and Purpose- We aimed to investigate the ability of machine learning (ML) techniques analyzing diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging to identify patients within the reco...