Critical Care

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

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Multimodal multi-task deep neural network framework for kinase-target prediction.

Kinase plays a significant role in various disease signaling pathways. Due to the highly conserved s...

Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study.

OBJECTIVES: To compare the artificial intelligence algorithms as powerful machine learning methods f...

The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

In recent years, the machine learning research community has benefited tremendously from the availab...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modal...

MT-GCNN: Multi-Task Learning with Gated Convolution for Multiple Transmitters Localization in Urban Scenarios.

With the advance of the Internet of things (IoT), localization is essential in varied services. In u...

MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images.

Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its sprea...

Self-Supervised Multi-Modal Hybrid Fusion Network for Brain Tumor Segmentation.

Accurate medical image segmentation of brain tumors is necessary for the diagnosing, monitoring, and...

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning.

Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive abilities. Rec...

Natural Language Processing Model for Identifying Critical Findings-A Multi-Institutional Study.

Improving detection and follow-up of recommendations made in radiology reports is a critical unmet n...

MODENN: A Shallow Broad Neural Network Model Based on Multi-Order Descartes Expansion.

Deep neural networks have achieved great success in almost every field of artificial intelligence. H...

MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition.

In the field of surface electromyography (sEMG) gesture recognition, how to improve recognition accu...

Deep label fusion: A generalizable hybrid multi-atlas and deep convolutional neural network for medical image segmentation.

Deep convolutional neural networks (DCNN) achieve very high accuracy in segmenting various anatomica...

ognitive utcomes in the ragmatic nvestigation of optimaxygen argets (CO-PILOT) trial: protocol and statistical analysis plan.

INTRODUCTION: Long-term cognitive impairment is one of the most common complications of critical ill...

Prediction of drug-target interactions through multi-task learning.

Identifying the binding between the target proteins and molecules is essential in drug discovery. Th...

Detection of arrhythmia in 12-lead varied-length ECG using multi-branch signal fusion network.

Automatic detection of arrhythmia based on electrocardiogram (ECG) plays a critical role in early pr...

In-sensor neural network for high energy efficiency analog-to-information conversion.

This work presents an on-chip analog-to-information conversion technique that utilizes analog hyper-...

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