Critical Care

Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning.

PURPOSE: To introduce a model that describes the effects of rigid translation due to respiratory mot...

Haemodynamic and respiratory perioperative outcomes for open versus robot-assisted radical cystectomy: A double-blinded, randomised trial.

BACKGROUND: The clinical impact of prolonged steep Trendelenburg position and CO pneumoperitoneum du...

WMNN: Wearables-Based Multi-Column Neural Network for Human Activity Recognition.

In recent years, human activity recognition (HAR) technologies in e-health have triggered broad inte...

Multi-Task and Few-Shot Learning-Based Fully Automatic Deep Learning Platform for Mobile Diagnosis of Skin Diseases.

Fluorescence imaging-based diagnostic systems have been widely used to diagnose skin diseases due to...

Clustering of critically ill patients using an individualized learning approach enables dose optimization of mobilization in the ICU.

BACKGROUND: While early mobilization is commonly implemented in intensive care unit treatment guidel...

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal pat...

Database-based machine learning in sepsis deserves attention.

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine.

With biotechnological advancements, innovative omics technologies are constantly emerging that have ...

Multi-Scale Histogram-Based Probabilistic Deep Neural Network for Super-Resolution 3D LiDAR Imaging.

LiDAR (Light Detection and Ranging) imaging based on SPAD (Single-Photon Avalanche Diode) technology...

Multi-task deep learning for medical image computing and analysis: A review.

The renaissance of deep learning has provided promising solutions to various tasks. While convention...

Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images.

Understanding prognosis and mortality is critical for evaluating the treatment plan of patients. Adv...

An accurate deep learning model for wheezing in children using real world data.

Auscultation is an important diagnostic method for lung diseases. However, it is a subjective modali...

Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning.

Accurate and efficient methods for identifying and tracking each animal in a group are needed to stu...

Predicting Genetic Disorder and Types of Disorder Using Chain Classifier Approach.

Genetic disorders are the result of mutation in the deoxyribonucleic acid (DNA) sequence which can b...

A Novel Deep Learning Model Based on Multi-Scale and Multi-View for Detection of Pulmonary Nodules.

Lung cancer manifests as pulmonary nodules in the early stage. Thus, the early and accurate detectio...

A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.

Multiple Sclerosis (MS) is an autoimmune disease that causes brain and spinal cord lesions, which ma...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Bioacoustic research spans a wide range of biological questions and applications, relying on identif...

A Novel Hybrid Multi-Modal Deep Learning for Detecting Hashtag Incongruity on Social Media.

Hashtags have been an integral element of social media platforms over the years and are widely used ...

Multi-Task Learning Model for Kazakh Query Understanding.

Query understanding (QU) plays a vital role in natural language processing, particularly in regard t...

Enhancing traditional Chinese medicine diagnostics: Integrating ontological knowledge for multi-label symptom entity classification.

In traditional Chinese medicine (TCM), artificial intelligence (AI)-assisted syndrome differentiatio...

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training.

Hypoxic ischemic encephalopathy (HIE) is a major global cause of neonatal death and lifelong disabil...