Hospital-Based Medicine

Intensivists

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

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Deep Multi-Magnification Networks for multi-class breast cancer image segmentation.

Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the...

Automatic Cephalometric Landmark Identification System Based on the Multi-Stage Convolutional Neural Networks with CBCT Combination Images.

This study was designed to develop and verify a fully automated cephalometry landmark identification...

Machine learning and statistics to qualify environments through multi-traits in Coffea arabica.

Several factors such as genotype, environment, and post-harvest processing can affect the responses ...

Multi disease-prediction framework using hybrid deep learning: an optimal prediction model.

Big data and its approaches are generally helpful for healthcare and biomedical sectors for predicti...

Multi-Domain Adversarial Feature Generalization for Person Re-Identification.

With the assistance of sophisticated training methods applied to single labeled datasets, the perfor...

Interpreting a recurrent neural network's predictions of ICU mortality risk.

Deep learning has demonstrated success in many applications; however, their use in healthcare has be...

3D multi-scale deep convolutional neural networks for pulmonary nodule detection.

With the rapid development of big data and artificial intelligence technology, computer-aided pulmon...

Multi-Scale Self-Guided Attention for Medical Image Segmentation.

Even though convolutional neural networks (CNNs) are driving progress in medical image segmentation,...

On the regularization of feature fusion and mapping for fast MR multi-contrast imaging via iterative networks.

Multi-contrast (MC) Magnetic Resonance Imaging (MRI) of the same patient usually requires long scann...

The Combined Effects of Sports Smart Bracelet and Multi-Component Exercise Program on Exercise Motivation among the Elderly in Macau.

Faced with the serious problem of an aging population, exercise is one of the most effective ways t...

Multi-objective optimization methods in novel drug design.

: In multi-objective drug design, optimization gains importance, being upgraded to a discipline that...

Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit.

Traditional Machine Learning (ML) models have had limited success in predicting Coronoavirus-19 (COV...

Safety critical event prediction through unified analysis of driver and vehicle volatilities: Application of deep learning methods.

Transportation safety is highly correlated with driving behavior, especially human error playing a k...

Generative Restricted Kernel Machines: A framework for multi-view generation and disentangled feature learning.

This paper introduces a novel framework for generative models based on Restricted Kernel Machines (R...

Exploration of swimming performance for a biomimetic multi-joint robotic fish with a compliant passive joint.

In this paper, a novel compliant joint with two identical torsion springs is proposed for a biomimet...

Multi-scale approach for the prediction of atomic scale properties.

Electronic nearsightedness is one of the fundamental principles that governs the behavior of condens...

Moderate to severe leukocytosis with vasopressor use is associated with increased mortality in trauma patients.

BACKGROUND: Leukocytosis is a rise in white blood cell (WBC) count and clinical outcomes of moderate...

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost.

BACKGROUND: Sepsis is a significant cause of mortality in-hospital, especially in ICU patients. Earl...

MD-NDNet: a multi-dimensional convolutional neural network for false-positive reduction in pulmonary nodule detection.

Pulmonary nodule false-positive reduction is of great significance for automated nodule detection in...

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