Hospital-Based Medicine

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

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Showing 2122-2142 of 6,177 articles
Retrospective Observational Study of the Clinical Performance Characteristics of a Machine Learning Approach to Early Sepsis Identification.

UNLABELLED: To estimate performance characteristics and impact on care processes of a machine learni...

Multi-task learning for quality assessment of fetal head ultrasound images.

It is essential to measure anatomical parameters in prenatal ultrasound images for the growth and de...

Multi-criteria group decision making based on Archimedean power partitioned Muirhead mean operators of q-rung orthopair fuzzy numbers.

Two critical tasks in multi-criteria group decision making (MCGDM) are to describe criterion values ...

RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification.

The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. Howev...

Multi optimized SVM classifiers for motor imagery left and right hand movement identification.

EEG signal can be a good alternative for disabled persons who cannot perform actions or perform them...

Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.

OBJECTIVE: To present a deep learning-based approach for semi-automatic prostate cancer classificati...

A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification.

One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled electroe...

A Hierarchical Neural Network for Sleep Stage Classification Based on Comprehensive Feature Learning and Multi-Flow Sequence Learning.

Automatic sleep staging methods usually extract hand-crafted features or network trained features fr...

FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule.

DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the dete...

Adversarial learning for mono- or multi-modal registration.

This paper introduces an unsupervised adversarial similarity network for image registration. Unlike ...

Predicting sepsis with a recurrent neural network using the MIMIC III database.

OBJECTIVE: Predicting sepsis onset with a recurrent neural network and performance comparison with I...

Multi-representation adaptation network for cross-domain image classification.

In image classification, it is often expensive and time-consuming to acquire sufficient labels. To s...

Multi-source sequential knowledge regression by using transfer RNN units.

Transfer learning has achieved a lot of success in deep neural networks to reuse useful knowledge fr...

ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU.

To improve the performance of Intensive Care Units (ICUs), the field of bio-statistics has developed...

Multi-view learning-based data proliferator for boosting classification using highly imbalanced classes.

BACKGROUND: Multi-view data representation learning explores the relationship between the views and ...

Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis.

Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung nodule is of...

Accurate automated Cobb angles estimation using multi-view extrapolation net.

Accurate automated quantitative Cobb angle estimation that quantitatively evaluates scoliosis plays ...

HetEnc: a deep learning predictive model for multi-type biological dataset.

BACKGROUND: Researchers today are generating unprecedented amounts of biological data. One trend in ...

Compressed sensing MRI via a multi-scale dilated residual convolution network.

Magnetic resonance imaging (MRI) reconstruction is an active inverse problem which can be addressed ...

Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis.

To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and...

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