Critical Care

A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.

Multiple Sclerosis (MS) is an autoimmune disease that causes brain and spinal cord lesions, which magnetic resonance imaging (MRI) can detect and characterize. Recently, deep learning methods have achieved remarkable results in the automated segmentation of MS lesions from MRI data. Hence, this study proposes a novel dense residual U-Net model that combines attention gate (AG), efficient channel a...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensive, error-prone, and becomes unfeasible with large data volumes. Therefore, machine-driven algorithms are increasingly applied to various bioacoustic ...

An implantable soft robotic ventilator augments inspiration in a pig model of respiratory insufficiency.

Severe diaphragm dysfunction can lead to respiratory failure and to the need for permanent mechanical ventilation. Yet permanent tethering to a mechan...

Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, mul...

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection.

Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are many existing works of early sepsis prediction us...

Artificial Intelligence for Clinical Interpretation of Bedside Chest Radiographs.

Background Supine chest radiography for bedridden patients in intensive care units (ICUs) is one of the most frequently ordered imaging studies worldw...

Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography-A Narrative Review.

Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activi...

Deetect: A Deep Learning-Based Image Analysis Tool for Quantification of Adherent Cell Populations on Oxygenator Membranes after Extracorporeal Membrane Oxygenation Therapy.

The strong interaction of blood with the foreign surface of membrane oxygenators during ECMO therapy leads to adhesion of immune cells on the oxygenat...

Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series.

Tree-based machine learning methods have gained traction in the statistical and data science fields. They have been shown to provide better solutions ...

Characterizing Macrophages Diversity in COVID-19 Patients Using Deep Learning.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affec...

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing lung damage. AI-powered predictive models could b...

Mortality prediction in ICU Using a Stacked Ensemble Model.

Artificial intelligence (AI) technology has huge scope in developing models to predict the survival rate of critically ill patients in the intensive c...

A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards the Internet of Things (IoT), which has made life ...

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intell...

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis.

BACKGROUND: Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be d...

A systematic review: Chest radiography images (X-ray images) analysis and COVID-19 categorization diagnosis using artificial intelligence techniques.

COVID-19 pandemic created a turmoil across nations due to Severe Acute Respiratory Syndrome Corona virus-1(SARS - Co-V-2). The severity of COVID-19 sy...

Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients.

In recent years, machine learning methods have been rapidly adopted in the medical domain. However, current state-of-the-art medical mining methods us...

A Fuzzy Neural Network-Based Evaluation Method for Physical Education Teaching Management in Colleges.

A novel Fuzzy Neural Network (FNN) teaching quality assessment model of physical education (PE) is presented at colleges and universities to enhance t...

Invited Commentary: Postoperative Artificial Intelligence Model for ICU Triage.

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.

Exercise-induced pulmonary hemorrhage (EIPH) is a relevant respiratory disease in sport horses, which can be diagnosed by examination of bronchoalveol...