Intensivists

Novel Preoperative Risk Stratification Using Digital Phenotyping Applying a Scalable Machine-Learning Approach.

BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation,...

Real-Time Robotic Presentation Skill Scoring Using Multi-Model Analysis and Fuzzy Delphi-Analytic Hierarchy Process.

Existing methods for scoring student presentations predominantly rely on computer-based implementati...

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.

Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may i...

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...

Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling.

Extracting the rules of real-world multi-agent behaviors is a current challenge in various scientifi...

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...

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...

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...

Optimizing artificial intelligence in sepsis management: Opportunities in the present and looking closely to the future.

Sepsis remains a major challenge internationally for healthcare systems. Its incidence is rising due...

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...

The application of artificial intelligence in the management of sepsis.

Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to healthcare worldw...

General anesthesia enhances lesion quality and ablation efficiency of circumferential pulmonary vein isolation.

BACKGROUND: Pulmonary vein isolation (PVI) is the cornerstone of atrial fibrillation (AF) ablation. ...

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...

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...

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...

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.

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) pati...

Environmental force sensing helps robots traverse cluttered large obstacles.

Robots can traverse sparse obstacles by sensing environmental geometry and avoiding contact with obs...

Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.

Delirium is a syndrome of acute brain failure which is prevalent amongst older adults in the Intensi...