Critical Care

Multi-attribute decision-making method based on q-rung orthopair probabilistic hesitant fuzzy schweizer-sklar power weighted hamy mean operator.

In order to further improve the computing power of the information aggregation operator in the q-run...

Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning.

Automatic respiration monitoring of dairy cows in modern farming not only helps to reduce manual lab...

A fair experimental comparison of neural network architectures for latent representations of multi-omics for drug response prediction.

BACKGROUND: Recent years have seen a surge of novel neural network architectures for the integration...

LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion sig...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early...

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

PURPOSE: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher ...

DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics.

Modern oncology offers a wide range of treatments and therefore choosing the best option for particu...

Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

To evaluate the performance of machine learning (ML) models and to compare it with logistic regressi...

Artificial intelligence in multi-objective drug design.

The factors determining a drug's success are manifold, making de novo drug design an inherently mult...

Video gaming improves robotic surgery simulator success: a multi-clinic study on robotic skills.

We aimed to investigate the effects of video game habits, duration of experience, and training in di...

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization.

The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of h...

Conventional Versus Artificial Intelligence-Assisted Interpretation of Chest Radiographs in Patients With Acute Respiratory Symptoms in Emergency Department: A Pragmatic Randomized Clinical Trial.

OBJECTIVE: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can...

UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping.

Recent advances in unmanned aerial vehicles (UAV), mini and mobile sensors, and GeoAI (a blend of ge...

Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.

The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific communit...

Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

One of the major threats to marine ecosystems is pollution, particularly, that associated with the o...

Cross-Domain Echocardiography Segmentation with Multi-Space Joint Adaptation.

The segmentation of the left ventricle endocardium (LV) and the left ventricle epicardium (LV) in ec...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. T...

Artificial Intelligence and Machine Learning in Dialysis: Ready for Prime Time?

Multi-omics integration method based on attention deep learning network for biomedical data classification.

BACKGROUND AND OBJECTIVE: Integrating multi-omics data for the comprehensive analysis of the biologi...

Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.

In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or...

Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation.

BACKGROUND: Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the co...