Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Multi-Classification of Complex Microseismic Waveforms Using Convolutional Neural Network: A Case Study in Tunnel Engineering.

Due to the complexity of the various waveforms of microseismic data, there are high requirements on ...

A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer.

Deep learning has shown its great potential in the field of image classification due to its powerful...

Predicting Human Intention-Behavior Through EEG Signal Analysis Using Multi-Scale CNN.

At present, the application of Electroencephalogram (EEG) signal classification to human intention-b...

Multi-Scale Capsule Network for Predicting DNA-Protein Binding Sites.

Discovering DNA-protein binding sites, also known as motif discovery, is the foundation for further ...

Predicting TF-DNA Binding Motifs from ChIP-seq Datasets Using the Bag-Based Classifier Combined With a Multi-Fold Learning Scheme.

The rapid development of high-throughput sequencing technology provides unique opportunities for stu...

A Multi-Scale Activity Transition Network for Data Translation in EEG Signals Decoding.

Electroencephalogram (EEG) is a non-invasive collection method for brain signals. It has broad prosp...

Multi-Source Transfer Learning Via Multi-Kernel Support Vector Machine Plus for B-Mode Ultrasound-Based Computer-Aided Diagnosis of Liver Cancers.

B-mode ultrasound (BUS) imaging is a routine tool for diagnosis of liver cancers, while contrast-enh...

The Future Role of High-Performance Computing in Cardiovascular Medicine and Science -Impact of Multi-Dimensional Data Analysis.

Advances in High-performance computing (HPC) technology have reached the capacity to inform cardiova...

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients.

The combination of machine learning (ML) and electronic health records (EHR) data may be able to imp...

3D multi-scale, multi-task, and multi-label deep learning for prediction of lymph node metastasis in T1 lung adenocarcinoma patients' CT images.

The diagnosis of preoperative lymph node (LN) metastasis is crucial to evaluate possible therapy opt...

Multi-Robot Preemptive Task Scheduling with Fault Recovery: A Novel Approach to Automatic Logistics of Smart Factories.

This paper presents a novel approach for Multi-Robot Task Allocation (MRTA) that introduces priority...

Transhiatal robot-assisted minimally invasive esophagectomy: unclear benefits compared to traditional transhiatal esophagectomy.

Esophagectomy is a high-risk operation, regardless of technique. Minimally invasive transthoracic es...

Gait and locomotion analysis of a soft-hybrid multi-legged modular miniature robot.

The locomotion performance of the current legged miniature robots remains inferior compared to even ...

Improving Ponzi Scheme Contract Detection Using Multi-Channel TextCNN and Transformer.

With the development of blockchain technologies, many Ponzi schemes disguise themselves under the ve...

Short-term and pathologic outcomes of robotic versus open pancreatoduodenectomy for periampullary and pancreatic head malignancy: an early experience.

Open pancreatoduodenectomy (OPD) is associated with high perioperative morbidity. Adoption of robot-...

FluNet: An AI-Enabled Influenza-Like Warning System.

Influenza is an acute viral respiratory disease that is currently causing severe financial and resou...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (AD...

Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm.

Evaporation is a crucial component to be established in agriculture management and water engineering...

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