Critical Care

Deviation-support based fuzzy ensemble of multi-modal deep learning classifiers for breast cancer prognosis prediction.

Breast cancer is the fifth leading cause of death in females worldwide. Early detection and treatmen...

m5UMCB: Prediction of RNA 5-methyluridine sites using multi-scale convolutional neural network with BiLSTM.

As a prevalent RNA modification, 5-methyluridine (mU) plays a critical role in diverse biological pr...

Distributed deep reinforcement learning based on bi-objective framework for multi-robot formation.

Improving generalization ability in multi-robot formation can reduce repetitive training and calcula...

Multi-domain and complex protein structure prediction using inter-domain interactions from deep learning.

Accurately capturing domain-domain interactions is key to understanding protein function and designi...

The effect and exploration of continuous positive pressure ventilation combined with upper limb robot training on upper limb function in stroke patients with OSAHS.

FIT-graph: A multi-grained evolutionary graph based framework for disease diagnosis.

Early assessment, with the help of machine learning methods, can aid clinicians in optimizing the di...

Empowering COVID-19 detection: Optimizing performance through fine-tuned EfficientNet deep learning architecture.

The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of ind...

Comparison of the efficacy and safety of single-port versus multi-port robotic total mesorectal excision for rectal cancer: A propensity score-matched analysis.

BACKGROUND: It is unknown whether the da Vinci single-port system performs similarly to the previous...

DM-CNN: Dynamic Multi-scale Convolutional Neural Network with uncertainty quantification for medical image classification.

Convolutional neural network (CNN) has promoted the development of diagnosis technology of medical i...

Deep learning-based multi-stage postoperative type-b aortic dissection segmentation using global-local fusion learning.

Type-b aortic dissection (AD) is a life-threatening cardiovascular disease and the primary treatment...

Hybrid deep learning models with multi-classification investor sentiment to forecast the prices of China's leading stocks.

The prediction of stock prices has long been a captivating subject in academic research. This study ...

Microchip Versus Piezoelectric Point of Care Ultrasonography for Pulmonary and Vena Cava Evaluation in Patients With Acute Kidney Injury.

INTRODUCTION: Point-of-care ultrasonography (POCUS) has emerged as an important tool for examining c...

European Nephrologists' Attitudes toward the Application of Artificial Intelligence in Clinical Practice: A Comprehensive Survey.

INTRODUCTION: The rapid advancement of artificial intelligence and big data analytics, including des...

Cardiac Specific Troponin I as Prognostic Factor among Non-COVID-19 Mechanically Ventilated Patients in a Tertiary Government Hospital: A Prospective Study.

OBJECTIVE: The study aimed to investigate the relationship between cardiac Troponin I (cTnI) level a...

Robotic tomographic ultrasound and artificial intelligence for management of haemodialysis arteriovenous fistulae.

BACKGROUND: Arteriovenous fistulae (AVF) and Arteriovenous Grafts (AVG) may present a problematic va...

LM-Net: A light-weight and multi-scale network for medical image segmentation.

Current medical image segmentation approaches have limitations in deeply exploring multi-scale infor...

Flexible Gel-Free Multi-Modal Wireless Sensors With Edge Deep Learning for Detecting and Alerting Freezing of Gait Symptom.

Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease (PD). This work develops fle...

Antibiotics, Sedatives, and Catecholamines Further Compromise Sepsis-Induced Immune Suppression in Peripheral Blood Mononuclear Cells.

OBJECTIVES: We hypothesized that the immunosuppressive effects associated with antibiotics, sedative...

Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote mo...

Multi-Adaptive Optimization for multi-task learning with deep neural networks.

Multi-task learning is a promising paradigm to leverage task interrelations during the training of d...

Artificial intelligence and the Internet of Medical Things in the ICU: Time for implementation.