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Cubature Kalman Filter Based Training of Hybrid Differential Equation Recurrent Neural Network Physiological Dynamic Models.

Modeling biological dynamical systems is challenging due to the interdependence of different system ...

Machine learning for identifying resistance features of using whole-genome sequence single nucleotide polymorphisms.

, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance...

Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training.

In this paper, we introduce the , a nonconvex, yet analytically tractable, optimization program, in ...

Training for object recognition with increasing spatial frequency: A comparison of deep learning with human vision.

The ontogenetic development of human vision and the real-time neural processing of visual input exhi...

Effect of robotic-assisted gait training on functional status, walking and quality of life in complete spinal cord injury.

The purpose of this study was to investigate the effect of robotic-assisted gait training (RAGT) on ...

Diverse Deep Neural Networks All Predict Human Inferior Temporal Cortex Well, After Training and Fitting.

Deep neural networks (DNNs) trained on object recognition provide the best current models of high-le...

Predicting Kidney Discard Using Machine Learning.

BACKGROUND: Despite the kidney supply shortage, 18%-20% of deceased donor kidneys are discarded annu...

Towards automatic diagnosis of rheumatic heart disease on echocardiographic exams through video-based deep learning.

OBJECTIVE: Rheumatic heart disease (RHD) affects an estimated 39 million people worldwide and is the...

Robotics in Spine Surgery and Spine Surgery Training.

The increasing interest and advancements in robotic spine surgery parallels a growing emphasis on ma...

Comment on: Shortening surgical training through robotics: randomized clinical trial of laparoscopic versus robotic surgical learning curves.

Exploiting the power of information in medical education.

The explosion of medical information demands a thorough reconsideration of medical education, includ...

The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.

Covering: up to the end of 2020. The machine learning field can be defined as the study and applicat...

Skip-Connected Self-Recurrent Spiking Neural Networks With Joint Intrinsic Parameter and Synaptic Weight Training.

As an important class of spiking neural networks (SNNs), recurrent spiking neural networks (RSNNs) p...

Performance and educational training of radiographers in lung nodule or mass detection: Retrospective comparison with different deep learning algorithms.

The aim of this investigation was to compare the diagnostic performance of radiographers and deep le...

Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity.

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of ...

Data Vizualization Dashboards in Robotic Rehabilitation.

Robotic rehabilitation can offer effective solutions, facilitating physiotherapist work, and helping...

Robotic-Assisted Surgery Training (RAST) Program: An Educational Research Protocol.

Technology has had a dramatic impact on how diseases are diagnosed and treated. Although cut, sew, a...

Training and validation of a deep learning architecture for the automatic analysis of coronary angiography.

BACKGROUND: In recent years, the use of deep learning has become more commonplace in the biomedical ...

Comparisons between Locomat and Walkbot robotic gait training regarding balance and lower extremity function among non-ambulatory chronic acquired brain injury survivors.

Lower limb rehabilitation exoskeleton robots connect with the human body in a wearable way and contr...

Fluorescence microscopy datasets for training deep neural networks.

BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. ...

On training targets for deep learning approaches to clean speech magnitude spectrum estimation.

Estimation of the clean speech short-time magnitude spectrum (MS) is key for speech enhancement and ...