Critical Care

Emerging Biomarkers and Advanced Diagnostics in Chronic Kidney Disease: Early Detection Through Multi-Omics and AI.

Chronic kidney disease (CKD) remains a significant global health burden, often diagnosed at advanced...

The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis.

BACKGROUND: The Surviving Sepsis Campaign strongly recommends that all hospitals screen for sepsis a...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to variou...

Correction: Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T solar systems.

Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization.

Multi-label classification is a significant challenge in machine learning, especially as the dimensi...

Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a critical condition commonly encountered ...

An automated cascade framework for glioma prognosis via segmentation, multi-feature fusion and classification techniques.

Glioma is one of the most lethal types of brain tumors, accounting for approximately 33% of all diag...

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

This article describes the staged restructure of the rapid response program into a dedicated 24/7 pr...

[Chest radiological lesions in COVID-19 : from classical imaging to artificial intelligence].

In the course of the pandemic induced by the appearance of a new coronavirus (SARS-CoV-2; COVID-19) ...

Development, Validation, and Deployment of a Time-Dependent Machine Learning Model for Predicting One-Year Mortality Risk in Critically Ill Patients with Heart Failure.

Heart failure (HF) ranks among the foremost causes of mortality globally, exhibiting particularly h...

Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients.

Intradialytic hypotension (IDH) is a critical complication in patients with chronic kidney disease u...

Investigation of Bleeding Disorders: When and How Should We Test Platelet Functions?

Inherited platelet disorders (IPDs) are rare conditions with diverse underlying pathophysiology whic...

GAMMNet: Gating Multi-head Attention in a Multi-modal Deep Network for Sound Based Respiratory Disease Detection.

Respiratory diseases present significant challenges to global health due to their high morbidity and...

Paradigm-Shifting Attention-based Hybrid View Learning for Enhanced Mammography Breast Cancer Classification with Multi-Scale and Multi-View Fusion.

Breast cancer poses a serious threat to women's health, and its early detection is crucial for enhan...

Mitigating Bias in Machine Learning Models with Ethics-Based Initiatives: The Case of Sepsis.

This paper discusses ethics-based strategies for mitigating bias in machine learning models used to ...

IFPTML Multi-Output Model for Anti-Retroviral Compounds Including the Drug Structure and Target Protein Sequence Information.

Retroviruses such as HIV cause significant diseases in humans and other organisms, making the discov...

A scalable deep attention mechanism of instance segmentation for the investigation of chromosome.

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and g...

Learning-based multi-material CBCT image reconstruction with ultra-slow kV switching.

ObjectiveThe purpose of this study is to perform multiple () material decomposition with deep learni...

Hybrid Series of Carbon-Vacancy Electrodes for Multi Chemical Vapors Diagnosis Using a Residual Multi-Task Model.

Detecting individual gases with various sensors is a well-established field in gas sensing. However,...

Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage.

Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates ...

Optimizing sustainable blended concrete mixes using deep learning and multi-objective optimization.

The proposed framework unites deep neural networks (DNNs) together with multi-objective optimization...