Care of terminally ill / Palliative care

Hiding a plane with a pixel: examining shape-bias in CNNs and the benefit of building in biological constraints.

When deep convolutional neural networks (CNNs) are trained "end-to-end" on raw data, some of the feature detectors they develop in their early layers resemble the representations found in early visual cortex. This result has been used to draw parallels between deep learning systems and human visual perception. In this study, we show that when CNNs are trained end-to-end they learn to classify imag...

User-Centered Design of a Mobile Health Intervention to Enhance Exacerbation-Related Self-Management in Patients With Chronic Obstructive Pulmonary Disease (Copilot): Mixed Methods Study.

BACKGROUND: Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impact of COPD exacerbations. Using mobile health (mHealth) to support exacerbation-related self-management could be promising in engaging patients in their own health and changing health behaviors. However, there is limited knowledge on how to design mHe...

Machine-learning-based diagnostics of EEG pathology.

Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted featu...

Amino acid encoding for deep learning applications.

BACKGROUND: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over c...

An end-to-end exemplar association for unsupervised person Re-identification.

Tracklet association methods learn the cross camera retrieval ability though associating underlying cross camera positive samples, which have proven t...

Integrating 3D Model Representation for an Accurate Non-Invasive Assessment of Pressure Injuries with Deep Learning.

Pressure injuries represent a major concern in many nations. These wounds result from prolonged pressure on the skin, which mainly occur among elderly...

DeepDistance: A multi-task deep regression model for cell detection in inverted microscopy images.

This paper presents a new deep regression model, which we call DeepDistance, for cell detection in images acquired with inverted microscopy. This mode...

Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest.

Biomass and yield are key variables for assessing the production and performance of agricultural systems. Modeling and predicting the biomass and yiel...

Position and Force Control of a Soft Pneumatic Actuator.

Recent advances in robotic systems have increased the need for various kinds of robots in many fields, such as aerospace and medical. Utilizing hard r...

End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.

Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients. Continuous BP monitoring is important for patient...

Deep Multi-Scale Fusion Neural Network for Multi-Class Arrhythmia Detection.

Automated electrocardiogram (ECG) analysis for arrhythmia detection plays a critical role in early prevention and diagnosis of cardiovascular diseases...

End-to-End Deep Learning Fusion of Fingerprint and Electrocardiogram Signals for Presentation Attack Detection.

Although fingerprint-based systems are the commonly used biometric systems, they suffer from a critical vulnerability to a presentation attack (PA). T...

Review of Stereo Matching Algorithms Based on Deep Learning.

Stereo vision is a flourishing field, attracting the attention of many researchers. Recently, leveraging on the development of deep learning, stereo m...

Value of a Machine Learning Approach for Predicting Clinical Outcomes in Young Patients With Hypertension.

Risk stratification of young patients with hypertension remains challenging. Generally, machine learning (ML) is considered a promising alternative to...

An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis.

Automatic skin lesion analysis of dermoscopy images remains a challenging topic. In this paper, we propose an end-to-end multi-task deep learning fram...

On the localness modeling for the self-attention based end-to-end speech synthesis.

Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end...

Reconstruction of natural visual scenes from neural spikes with deep neural networks.

Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreove...

Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and gr...

DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.

BACKGROUND: Recently developed methods of protein contact prediction, a crucially important step for protein structure prediction, depend heavily on d...

A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks.

Human face image analysis is an active research area within computer vision. In this paper we propose a framework for face image analysis, addressing ...