Head Trauma

Rare Event Early Detection: A Dataset of Sepsis Onset for Critically Ill Trauma Patients

Sepsis is a major public health concern due to its high morbidity, mortality, and cost. Its clinical outcome can be substantially improved through early detection and timely intervention. By leveraging publicly available datasets, machine learning (ML) has driven advances in both research and clinical practice. However, existing public datasets consider ICU patients (Intensive Care Unit) as a unif...

Serum Proteomic Profiling Implicates a Dysregulated Neurohormonal-Inflammatory Axis in Post-Fontan Tachycardia

Background: Post-operative tachycardia is a common and poorly understood complication following the Fontan procedure. Post-operative factors such as surgical scarring and venous hypertension can contribute to tachycardia risk, but the specific molecular signaling cascades triggering acute tachycardia remain uncharacterized, limiting therapeutic innovation and leaving clinicians with limited strate...

Spatial mapping of RNA turnover kinetics and regulatory landscapes of mRNA stability in the mammalian brain

Spatial and activity-dependent gene regulation in the mammalian brain requires coordinated control of RNA synthesis and degradation, yet spatially res...

EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Transformers

Current generative video models excel at producing novel content from text and image prompts, but leave a critical gap in editing existing pre-recorde...

Neural Signatures of Post-Decision Outcome Expectation and Evaluation in Human Sensorimotor Choice Behavior

The concept of embodied sensorimotor decision-making proposes that processes implicated in evaluating sensory inputs and selecting appropriate motor a...

Context Patch Fusion With Class Token Enhancement for Weakly Supervised Semantic Segmentation

Weakly Supervised Semantic Segmentation (WSSS), which relies only on image-level labels, has attracted significant attention for its cost-effectivenes...

Concepts from Representations: Post-hoc Concept Bottleneck Models via Sparse Decomposition of Visual Representations

Deep learning has achieved remarkable success in image recognition, yet their inherent opacity poses challenges for deployment in critical domains. Co...

Leveraging Explainable Temporal-Modelling Machine Learning to Identify Distinct Multimorbidity Trajectory Profiles in Acute Myocardial Infarction

IntroductionAcute myocardial infarction (AMI) remains a leading cause of mortality, with the coexistence of other conditions (i.e., multimorbidity) co...

Prediction of peripheral blood lymphocyte subpopulations after renal transplantation.

Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs)...

Detection of S1 spike protein in CD16+ monocytes up to 245 days in SARS-CoV-2-negative post-COVID-19 vaccine syndrome (PCVS) individuals.

Despite over 13 billion SARS-CoV-2 vaccine doses administered globally, persistent post-vaccination symptoms, termed post-COVID-19 vaccine syndrome (P...

Progressive fine-to-coarse reconstruction for accurate low-bit post-training quantization in vision transformers.

Due to its efficiency, Post-Training Quantization (PTQ) has been widely adopted for compressing Vision Transformers (ViTs). However, when quantized in...

Advancement of an automatic segmentation pipeline for metallic artifact removal in post-surgical ACL MRI.

Magnetic resonance imaging (MRI) has the potential to identify post-operative risk factors for re-tearing an anterior cruciate ligament (ACL) using a ...

Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.

OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical ite...

Emotion Recognition in Older Adults with Quantum Machine Learning and Wearable Sensors

We investigate the feasibility of inferring emotional states exclusively from physiological signals, thereby presenting a privacy-preserving alterna...

Where are we with calibration under dataset shift in image classification?

We conduct an extensive study on the state of calibration under real-world dataset shift for image classification. Our work provides important insig...

TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation

Digital orthodontics represents a prominent and critical application of computer vision technology in the medical field. So far, the labor-intensive...

ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Sensing

Recent advancements in generative methods, especially diffusion models, have made great progress in remote sensing image synthesis. Despite these ad...

Automated anatomy-based post-processing reduces false positives and improved interpretability of deep learning intracranial aneurysm detection

Introduction: Deep learning (DL) models can help detect intracranial aneurysms on CTA, but high false positive (FP) rates remain a barrier to clinic...

MACHINE LEARNING AND SHOCK INDICES-DERIVED SCORE FOR PREDICTING CONTRAST-INDUCED NEPHROPATHY IN ACUTE CORONARY SYNDROME PATIENTS.

Background: Contrast-induced nephropathy (CIN) is a serious complication following acute coronary syndrome (ACS), leading to increased morbidity and m...

Integrative analyses of 16S rDNA sequencing and serum metabolomics demonstrate significant roles for the oral microbiota and serum metabolites in post-kidney transplant diabetes mellitus.

Oral microbiota and serum metabolites play crucial roles in diabetes, but their relationship with post-transplant diabetes mellitus (PTDM), a common c...