Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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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...

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-...

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...

Machine Learning Accelerated, High Throughput, Multi-Objective Optimization of Multiprincipal Element Alloys.

Multiprincipal element alloys (MPEAs) have gained surging interest due to their exceptional properti...

DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images.

Multi-modal medical image fusion is a challenging yet important task for precision diagnosis and sur...

A Combinatorial Deep Learning Structure for Precise Depth of Anesthesia Estimation From EEG Signals.

Electroencephalography (EEG) is commonly used to measure the depth of anesthesia (DOA) because EEG r...

Evolutionary Multi-Objective One-Shot Filter Pruning for Designing Lightweight Convolutional Neural Network.

Deep neural networks have achieved significant development and wide applications for their amazing p...

Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping.

Cosegmentation is a newly emerging computer vision technique used to segment an object from the back...

Multi-model fusion of classifiers for blood pressure estimation.

Prehypertension is a new risky disease defined in the seventh report issued by the Joint National Co...

Improved protein relative solvent accessibility prediction using deep multi-view feature learning framework.

The accurate prediction of the relative solvent accessibility of a protein is critical to understand...

Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.

BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if ...

Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease Diagnosis With Structural MRI.

Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological disease diagn...

Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data.

With the recent advances in deep learning, wearable sensors have increasingly been used in automated...

Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems.

In this paper, an event-triggered control (ETC) method is investigated to solve zero-sum game (ZSG) ...

Two-phase non-invasive multi-disease detection via sublingual region.

Non-invasive multi-disease detection is an active technology that detects human diseases automatical...

Dual scope method: A novel application of a simultaneous multi-image display system for a thoracoscopic robotic lobectomy.

The advantages of a multi-input display system platform in robotic thoracic surgery have not been we...

Effective Point Cloud Analysis Using Multi-Scale Features.

Fully exploring the correlation of local features and their spatial distribution in point clouds is ...

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