Critical Care

Cardiac Specific Troponin I as Prognostic Factor among Non-COVID-19 Mechanically Ventilated Patients in a Tertiary Government Hospital: A Prospective Study.

OBJECTIVE: The study aimed to investigate the relationship between cardiac Troponin I (cTnI) level and prognosis among mechanically ventilated patients in terms of mortality, prolonged mechanical ventilation, and tracheostomy rate.

Robotic tomographic ultrasound and artificial intelligence for management of haemodialysis arteriovenous fistulae.

BACKGROUND: Arteriovenous fistulae (AVF) and Arteriovenous Grafts (AVG) may present a problematic vascular access for renal replacement therapy (RRT), reliant on recurrent specialist nurse and medical evaluation. Dysfunctional accesses are frequently referred 'out of the dialysis clinic' for specialist sonographic examination, with associated delays potentiating loss of vascular access viability a...

LM-Net: A light-weight and multi-scale network for medical image segmentation.

Current medical image segmentation approaches have limitations in deeply exploring multi-scale information and effectively combining local detail text...

Antibiotics, Sedatives, and Catecholamines Further Compromise Sepsis-Induced Immune Suppression in Peripheral Blood Mononuclear Cells.

OBJECTIVES: We hypothesized that the immunosuppressive effects associated with antibiotics, sedatives, and catecholamines amplify sepsis-associated im...

Real-time counting of wheezing events from lung sounds using deep learning algorithms: Implications for disease prediction and early intervention.

This pioneering study aims to revolutionize self-symptom management and telemedicine-based remote monitoring through the development of a real-time wh...

Multi-Adaptive Optimization for multi-task learning with deep neural networks.

Multi-task learning is a promising paradigm to leverage task interrelations during the training of deep neural networks. A key challenge in the traini...

Artificial intelligence and the Internet of Medical Things in the ICU: Time for implementation.

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (IC...

Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.

Delirium is a syndrome of acute brain failure which is prevalent amongst older adults in the Intensive Care Unit (ICU). Incidence of delirium can sign...

How AI is advancing asthma management? Insights into economic and clinical aspects.

Asthma, an increasingly prevalent chronic respiratory condition, incurs significant economic costs worldwide. Artificial Intelligence (AI), particular...

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine ...

Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion.

The rapid development of drugs against emerging and re-emerging viruses is required to prevent future pandemics. However, inhibitors usually take a lo...

Sleep Apnea Prediction Using Deep Learning.

Obstructive sleep apnea (OSA) is a sleep disorder that causes partial or complete cessation of breathing during an individual's sleep. Various methods...

Infra-Red Imaging to Detect Respirator Leak in Healthcare Workers During Fit-Testing Clinic.

OBJECTIVE: This study addressed the problem of objectively detecting leaks in P2 respirators at point of use, an essential component for healthcare wo...

The smarty4covid dataset and knowledge base as a framework for interpretable physiological audio data analysis.

Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respirator...

Application of Machine Learning Models to Biomedical and Information System Signals From Critically Ill Adults.

BACKGROUND: Machine learning (ML)-derived notifications for impending episodes of hemodynamic instability and respiratory failure events are interesti...

Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions.

Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networ...

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextension of healthcare. Both Chest X-rays (CXR) and blood...

Multi-Level Ethical Considerations of Artificial Intelligence Health Monitoring for People Living with Parkinson's Disease.

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system's ability to care f...

An event-triggered collaborative neurodynamic approach to distributed global optimization.

In this paper, we propose an event-triggered collaborative neurodynamic approach to distributed global optimization in the presence of nonconvexity. W...