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SkiNet: A deep learning framework for skin lesion diagnosis with uncertainty estimation and explainability.

Skin cancer is considered to be the most common human malignancy. Around 5 million new cases of skin...

Feasibility of transthoracic esophagectomy with a next-generation surgical robot.

Robot-assisted minimal access surgery (MAS), compared with conventional MAS, has shown a number of b...

Robotic cochlear implantation in post-meningitis ossified cochlea.

AIM: To report the experience of an image-guided and navigation-based robot arm as an assistive surg...

Real-Time Ship Segmentation in Maritime Surveillance Videos Using Automatically Annotated Synthetic Datasets.

This work proposes a new system capable of real-time ship instance segmentation during maritime surv...

Deploying deep learning models on unseen medical imaging using adversarial domain adaptation.

The fundamental challenge in machine learning is ensuring that trained models generalize well to uns...

Performance evaluation of deep learning-based post-processing and diagnostic reporting system for coronary CT angiography: a clinical comparative study.

A general deep learning framework for neuron instance segmentation based on Efficient UNet and morphological post-processing.

Recent studies have demonstrated the superiority of deep learning in medical image analysis, especia...

Methodology for Conducting Post-Marketing Surveillance of Software as a Medical Device Based on Artificial Intelligence Technologies.

UNLABELLED: was to develop a methodology for conducting post-registration clinical monitoring of so...

Interpretable deep learning for the prognosis of long-term functional outcome post-stroke using acute diffusion weighted imaging.

Advances in deep learning can be applied to acute stroke imaging to build powerful and explainable p...

Functional Gait Assessment Using Manual, Semi-Automated and Deep Learning Approaches Following Standardized Models of Peripheral Nerve Injury in Mice.

Objective: To develop a standardized model of stretch−crush sciatic nerve injury in mice, and to com...

Robotic Biofeedback for Post-Stroke Gait Rehabilitation: A Scoping Review.

This review aims to recommend directions for future research on robotic biofeedback towards prompt p...

Using Deep Learning to Predict Minimum Foot-Ground Clearance Event from Toe-Off Kinematics.

Efficient, adaptive, locomotor function is critically important for maintaining our health and indep...

Adverse events in the digital age and where to find them.

Exponential growth of health-related data collected by digital tools is a reality within pharmaceuti...

Novel neural network model for predicting susceptibility of facial post-inflammatory hyperpigmentation.

BACKGROUND: To construct a neural network model (ATBP) for predicting susceptibility to Post-inflamm...

Application of an EMG-Rehabilitation Robot in Patients with Post-Coronavirus Fatigue Syndrome (COVID-19)-A Feasibility Study.

This pilot study aimed to assess the safety and feasibility of an EMG-driven rehabilitation robot in...

Deep learning-based fully automatic segmentation of the maxillary sinus on cone-beam computed tomographic images.

The detection of maxillary sinus wall is important in dental fields such as implant surgery, tooth e...

Quantifying the post-radiation accelerated brain aging rate in glioma patients with deep learning.

BACKGROUND AND PURPOSE: Changes of healthy appearing brain tissue after radiotherapy (RT) have been ...

A real-time object detection model for orchard pests based on improved YOLOv4 algorithm.

Accurate and efficient real-time detection of orchard pests was essential and could improve the econ...

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection.

The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which...

An interpretable neural network for outcome prediction in traumatic brain injury.

BACKGROUND: Traumatic Brain Injury (TBI) is a common condition with potentially severe long-term com...

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.

We sought to craft a drug safety signalling pipeline associating latent information in clinical free...