Hospital-Based Medicine

Intensivists

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

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ConF: A Deep Learning Model Based on BiLSTM, CNN, and Cross Multi-Head Attention Mechanism for Noncoding RNA Family Prediction.

This paper presents ConF, a novel deep learning model designed for accurate and efficient prediction...

Neurodynamic approaches for multi-agent distributed optimization.

This paper considers a class of multi-agent distributed convex optimization with a common set of con...

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and...

Lightweight Multi-Class Support Vector Machine-Based Medical Diagnosis System with Privacy Preservation.

Machine learning, powered by cloud servers, has found application in medical diagnosis, enhancing th...

Revisiting multi-view learning: A perspective of implicitly heterogeneous Graph Convolutional Network.

Graph Convolutional Network (GCN) has become a hotspot in graph-based machine learning due to its po...

Multi-Cat Monitoring System Based on Concept Drift Adaptive Machine Learning Architecture.

In multi-cat households, monitoring individual cats' various behaviors is essential for diagnosing t...

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextensio...

A multi-stage group decision making approach for sustainable supplier selection based on probabilistic linguistic time-ordered incentive operator.

This study proposes a novel multi-stage multi-attribute group decision making method under a probabi...

Learning Skill Training Schedules From Domain Experts for a Multi-Patient Multi-Robot Rehabilitation Gym.

A robotic gym with multiple rehabilitation robots allows multiple patients to exercise simultaneousl...

Multi-Level Ethical Considerations of Artificial Intelligence Health Monitoring for People Living with Parkinson's Disease.

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI...

Multi-scale feature selection network for lightweight image super-resolution.

Recently, many super-resolution (SR) methods based on convolutional neural networks (CNNs) have achi...

MLapRVFL: Protein sequence prediction based on Multi-Laplacian Regularized Random Vector Functional Link.

Protein sequence classification is a crucial research field in bioinformatics, playing a vital role ...

Temperature and haemodynamic effects of a 100 mL bolus of 20% albumin at room versus body temperature in cardiac surgery patients.

To study the temperature and haemodynamic effects of room versus body temperature 20% albumin fluid...

Chewing gum prophylaxis for postoperative nausea and vomiting in the intensive care unit: a pilot randomised controlled trial.

To test the effectiveness of chewing gum in the prophylaxis of postoperative nausea and vomiting (P...

[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, ...

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images.

We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign d...

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a...

MicroRNA-30a inhibits cell proliferation in a sepsis-induced acute kidney injury model by targeting the YAP-TEAD complex.

BACKGROUND: Acute kidney injury (AKI) is a primary feature of renal complications in patients with s...

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