Product Alert

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mechanisms and optimal management remain uncertain. Using computed tomography angiography (CTA), we present a feasibility workflow that integrates statistical shape analysis (SSA), computational hemodynamics, and machine learning (ML) to investigate pred...

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integr...

Lean mass loss in the intensive care unit and its restoration: A narrative review.

The preservation of lean mass (LM) and its restoration following catabolic loss represents a primary challenge for clinical nutrition in critically il...

Dynamic Ex-Post Baselines for Enhancing the Credibility of Improved Forest Management Carbon Offsets.

Forest carbon offsets are pivotal to the global climate strategy, yet their claimed benefits are often undermined by flawed baselines, compromising th...

A comprehensive review of non-destructive technologies for banana ripeness assessment: implications for food quality, safety, and supply chain management.

Banana (Musa spp.) is a primary climacteric fruit characterized by a rapid surge in ethylene production and respiration post-harvest. Accurate ripenes...

Reimagining intensive care unit recovery: The Critical Illness Survivorship Programme for humanising post-intensive care unit care - A discussion paper.

BACKGROUND: Survivorship after critical illness is often characterised by fragmented recovery and lingering cognitive, psychological, and physical imp...

A multimodal imaging dataset for quality grading of Canadian wild rice kernels using RGB and VNIR hyperspectral data.

This article presents a multimodal dataset of Canadian wild rice (Zizania palustris) kernels, combining high-resolution RGB imagery and visible-near-i...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

3D Cardiac Magnetic Resonance Substrate Features-Based Machine Learning Model for Post-myocardial Infarction Risk Stratification: a Multicenter Study.

BACKGROUND: Accurate risk stratification post-myocardial infarction (MI) remains challenging. This study aimed to develop interpretable machine learni...

Human in the loop artificial intelligence in healthcare: applications, outcomes, and implementation challenges.

BACKGROUND: The integration of artificial intelligence in healthcare has transformed clinical practice and research methodologies. However, concerns r...

Multi-branch convolutional neural network and intracranial EEG high-frequency oscillations predict post-surgical seizure outcomes.

OBJECTIVE: Pathological High-Frequency Oscillations (HFOs) identify epileptogenic cortex, but their surgical utility is unproven. Current epilepsy sur...

Active surveillance methods to identify adverse events of special interest (AESIs) following vaccination against pandemic diseases: A scoping review.

INTRODUCTION: Active post-vaccination surveillance is vital for ensuring vaccine safety, particularly in monitoring Adverse Events of Special Interest...

Post-treatment infection prediction in CLL using domain adaptation of lymphoma electronic health records.

BACKGROUND AND PURPOSE: Infections are the leading cause of morbidity and mortality in patients with chronic lymphocytic leukemia (CLL) and occur duri...

Interpretable Machine Learning for Stroke Recovery: Predicting Discharge and 3-Month Functional Outcomes.

IntroductionStroke is a leading cause of disability worldwide. This study uses Machine Learning models to investigate factors influencing modified Ran...

Efficacy and neural mechanisms of a vibrotactile-enhanced, brain-controlled soft robotic glove for upper limb rehabilitation after stroke: a multicentre randomised controlled trial protocol.

INTRODUCTION: Soft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demonstrated potential in facilitating motor recovery a...

Longitudinal brain-age predictions comprising long-duration spaceflight missions.

Our study investigates the effects of long-duration spaceflight on brain aging in spacefarers using structural MRI and machine learning models. Pre-, ...

Deep transfer learning based image colorization using VGG19 and CLAHE.

Image colorization transforms grayscale images into realistic color representations. It is a challenging area of research in computer vision due to un...

Predicting mycophenolic acid exposure in pediatric lupus nephritis: a real-world study across three clinical scenarios.

OBJECTIVES: Childhood-onset systemic lupus erythematosus (cSLE) with lupus nephritis (LN) presents therapeutic challenges due to complex mycophenolic ...

Characterising processing conditions that artifactually bias human brain tissue transcriptomes.

Autopsy-derived brain tissue analysis is crucial for understanding neurobiology, but post-mortem handling can introduce artifacts. We studied adult hu...

Identification and Validation of Liver Transplantation-Induced Acute Lung Injury Biomarkers Using a Bioinformatics and Experimental Approach.

BACKGROUND Acute lung injury (ALI) after liver transplantation (LT) is a critical complication negatively affecting transplant outcomes and patient su...