Care of terminally ill / Palliative care

Simple Convolutional-Based Models: Are They Learning the Task or the Data?

Convolutional neural networks (CNNs) evolved from Fukushima's neocognitron model, which is based on the ideas of Hubel and Wiesel about the early stages of the visual cortex. Unlike other branches of neocognitron-based models, the typical CNN is based on end-to-end supervised learning by backpropagation and removes the focus from built-in invariance mechanisms, using pooling not as a way to tolera...

Removing Noise from Extracellular Neural Recordings Using Fully Convolutional Denoising Autoencoders.

Extracellular recordings are severely contaminated by a considerable amount of noise sources, rendering the denoising process an extremely challenging task that should be tackled for efficient spike sorting. To this end, we propose an end-to-end deep learning approach to the problem, utilizing a Fully Convolutional Denoising Autoencoder, which learns to produce a clean neuronal activity signal fro...

End-to-End Versatile Human Activity Recognition with Activity Image Transfer Learning.

Transfer learning is a common solution to address cross-domain identification problems in Human Activity Recognition (HAR). Most existing approaches t...

End-To-End Bioluminescence Tomography Reconstruction Based On Convolution Neural Network Scheme.

Bioluminescence tomography (BLT) has received a lot of attention as an important technique in bio-optical imaging. Compared with traditional methods, ...

End-to-End Neural Network for Feature Extraction and Cancer Diagnosis of In Vivo Fluorescence Lifetime Images of Oral Lesions.

In contrast to previous studies that focused on classical machine learning algorithms and hand-crafted features, we present an end-to-end neural netwo...

An Improved Networked Predictive Controller for Vascular Robot Using 5G Networks.

Percutaneous coronary intervention (PCI) has gradually become the most common treatment of coronary artery disease (CAD) in clinical practice due to i...

Design of Novel End-effectors for Robot-assisted Swab Sampling to Combat Respiratory Infectious Diseases.

The COVID-19 outbreak has caused the mortality worldwide and the use of swab sampling is a common way of screening and diagnosis. To combat respirator...

Kinematic and Workspace Analysis of the Master Robot in the Sina Robotic Telesurgery System.

Robotic telesurgery systems, including master and slave robots, have emerged in recent years to provide benefits for both surgeons and patients. Surge...

Assistive Sliding Mode Control of a Rehabilitation Robot with Automatic Weight Adjustment.

There are approximately 13 million new stroke cases worldwide each year. Research has shown that robotics can provide practical and efficient solution...

An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction.

Accurately identifying potential drug-target interactions (DTIs) is a key step in drug discovery. Although many related experimental studies have been...

Deep learning-based stereophonic acoustic echo suppression without decorrelation.

Traditional stereophonic acoustic echo cancellation algorithms need to estimate acoustic echo paths from stereo loudspeakers to a microphone, which of...

Model Experimental Study of Man-Machine Interactive Robot-Assisted Craniotomy.

To evaluate the feasibility, safety, and accuracy of the new man-machine interactive robotic system in model experiment. The implantation of the 8 to ...

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 separation. Moreover, an automatic speech recognit...

Surgical management of secondary hyperparathyroidism in dialysis patients in Senegal.

Secondary hyperparathyroidism (SHPT) is a common complication of end-stage renal disease. Surgical management occurs in severe forms and/or unresponsi...

Predicting Age with Deep Neural Networks from Polysomnograms.

The aim of this study was to design a new deep learning framework for end-to-end processing of polysomnograms. This framework can be trained to analyz...

End-to-End Approach for Structuring Radiology Reports.

Radiology reports include various types of clinical information that are used for patient care. Reports are also expected to have secondary uses (e.g....

Investigating the Barriers to Physician Adoption of an Artificial Intelligence- Based Decision Support System in Emergency Care: An Interpretative Qualitative Study.

The development of artificial intelligence (AI) systems to support diagnostic decision-making is rapidly expanding in health care. However, important ...

[Heartbeat-based end-to-end classification of arrhythmias].

OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopi...

Radiology-Pathology Correlation to Facilitate Peer Learning: An Overview Including Recent Artificial Intelligence Methods.

Correlation of pathology reports with radiology examinations has long been of interest to radiologists and helps to facilitate peer learning. Such cor...

An End-to-end System for Automatic Characterization of Iba1 Immunopositive Microglia in Whole Slide Imaging.

Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. Detailed studies of the microglial response after TBI req...