Transplantation

Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.

Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent cells promotes chronic inflammation, tissue dysfunction, age-related diseases, and tumor suppression. Recent advancements in immunotherapy have positioned T cell-based approaches as precision tools for the targeted clearance of senescent cells, offerin...

Pancreas segmentation in CT scans: A novel MOMUNet based workflow.

Automatic pancreas segmentation in CT scans is crucial for various medical applications, including early diagnosis and computer-assisted surgery. However, existing segmentation methods remain suboptimal due to significant pancreas size variations across slices and severe class imbalance caused by the pancreas's small size and CT scanner movement during imaging. Traditional computer vision techniqu...

A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions.

Flow cytometry (FC) remains a cornerstone diagnostic tool for acute myeloid leukemia (AML), yet standardizing panels across laboratories presents pers...

Deep learning-based histopathologic segmentation of peritubular capillaries in kidney transplant biopsies.

BACKGROUND: Assessing the extent of inflammation in peritubular capillaries (PTCs) is important for diagnosing antibody-mediated rejection in kidney t...

Ultra-low-power System-on-Chip for automated screening of central apnea and hypopnea via chin electromyography.

Central Apnea (CA) and Central Hypopnea (CH) are sleep disorders arising from the brain's inability to signal respiratory muscles, potentially leading...

Cascade learning in multi-task encoder-decoder networks for concurrent bone segmentation and glenohumeral joint clinical assessment in shoulder CT scans.

Osteoarthritis is a degenerative condition that affects bones and cartilage, often leading to structural changes, including osteophyte formation, bone...

DFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications.

Resource recovery from textile wastewater has attracted increasing interest because it simultaneously addresses wastewater treatment and maximizes the...

Arch-Net: Model conversion and quantization for architecture agnostic model deployment.

The significant computational demands of Deep Neural Networks (DNNs) present a major challenge for their practical application. Recently, many Applica...

Mesenchymal stem cell transplantation ameliorates inflammation in spinal cord injury by inhibiting lactylation-related genes.

BACKGROUND: The immune microenvironment significantly influences neural regeneration in spinal cord injury (SCI). Lactate activates central nervous sy...

VOCAL: Visual Odometry via ContrAstive Learning

Breakthroughs in visual odometry (VO) have fundamentally reshaped the landscape of robotics, enabling ultra-precise camera state estimation that is ...

GroundingDINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models

Accurate and generalizable object segmentation in ultrasound imaging remains a significant challenge due to anatomical variability, diverse imaging ...

A High-Throughput Platform to Bench Test Smartphone-Based Heart Rate Measurements Derived From Video

Smartphone-based heart rate (HR) monitoring apps using finger-over-camera photoplethysmography (PPG) face significant challenges in performance eval...

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation

Multi-organ medical segmentation is a crucial component of medical image processing, essential for doctors to make accurate diagnoses and develop ef...

Scaling Out Chip Interconnect Networks with Implicit Sequence Numbers

As AI models outpace the capabilities of single processors, interconnects across chips have become a critical enabler for scalable computing. These ...

Universal Gluing and Contextual Choice: Categorical Logic and the Foundations of Analytic Approximation

We introduce a new categorical and constructive foundation for analytic approximation based on a Contextual Choice Principle (CCP), which enforces l...

Charge transfer at air-water interfaces: A machine learning potential-based molecular dynamics study.

Water at interfaces plays a crucial role in many natural processes and industrial applications. However, the relationship between water's hydrogen bon...

Improving Diffusion-Based Image Editing Faithfulness via Guidance and Scheduling

Text-guided diffusion models have become essential for high-quality image synthesis, enabling dynamic image editing. In image editing, two crucial a...

Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis.

With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes after allogeneic hematopoietic cell transplantati...

SABRE-FL: Selective and Accurate Backdoor Rejection for Federated Prompt Learning

Federated Prompt Learning has emerged as a communication-efficient and privacy-preserving paradigm for adapting large vision-language models like CL...

Personalized translational medicine: Investigating YKL-40 as early biomarker for clinical risk stratification in hepatocellular carcinoma recurrence post-liver transplantation.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) presents a significant challenge, with recurrence rates ranging from 8% to ...