Hospital-Based Medicine

Intensivists

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

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[Artificial Intelligence: Challenges and Applications in Intensive Care Medicine].

The high workload in intensive care medicine arises from the exponential growth of medical knowledge...

Multi-Class Skin Problem Classification Using Deep Generative Adversarial Network (DGAN).

The lack of annotated datasets makes the automatic detection of skin problems very difficult, which ...

Early identification of ICU patients at risk of complications: Regularization based on robustness and stability of explanations.

The aim of this study is to build machine learning models to predict severe complications using admi...

Artificial Intelligence in Infection Management in the ICU.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency M...

Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

This study was aimed at exploring the application of image segmentation based on full convolutional ...

Fermatean fuzzy ELECTRE multi-criteria group decision-making and most suitable biomedical material selection.

ELECTRE is a family of multi-criteria decision analysis techniques, which has the ability to provide...

Chinese clinical named entity recognition via multi-head self-attention based BiLSTM-CRF.

Clinical named entity recognition (CNER) is a fundamental step for many clinical Natural Language Pr...

Neuronal Apoptosis in Patients with Liver Cirrhosis and Neuronal Epileptiform Discharge Model Based upon Multi-Modal Fusion Deep Learning.

Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a cor...

A 3D Printed Soft Robotic Hand With Embedded Soft Sensors for Direct Transition Between Hand Gestures and Improved Grasping Quality and Diversity.

In this study, a three-dimensional (3D) printed soft robotic hand with embedded soft sensors, intend...

Automated diagnosis of age-related macular degeneration using multi-modal vertical plane feature fusion via deep learning.

PURPOSE: To develop a computer-aided diagnostic (CADx) system of age-related macular degeneration (A...

A novel ramp loss-based multi-task twin support vector machine with multi-parameter safe acceleration.

Direct multi-task twin support vector machine (DMTSVM) is an effective algorithm to deal with multi-...

A novel multi-objective medical feature selection compass method for binary classification.

The use of Artificial Intelligence in medical decision support systems has been widely studied. Sinc...

A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, cal...

Viewport-Based CNN: A Multi-Task Approach for Assessing 360° Video Quality.

For 360° video, the existing visual quality assessment (VQA) approaches are designed based on either...

A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics.

Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose...

Systematic Review and Comparison of Publicly Available ICU Data Sets-A Decision Guide for Clinicians and Data Scientists.

OBJECTIVE: As data science and artificial intelligence continue to rapidly gain traction, the public...

Identifying the Strength Level of Objects' Tactile Attributes Using a Multi-Scale Convolutional Neural Network.

In order to solve the problem in which most currently existing research focuses on the binary tactil...

Towards improving fast adversarial training in multi-exit network.

Adversarial examples are usually generated by adding adversarial perturbations on clean samples, des...

Smart Contract Vulnerability Detection Model Based on Multi-Task Learning.

The key issue in the field of smart contract security is efficient and rapid vulnerability detection...

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