Pathology

Multimodal artificial intelligence (AI) for estimating the sinking velocity of microplastic-microalgae aggregates using explainable AI and visualization.

Microplastics are pervasive pollutants in marine environments that interact with microalgae to form microplastic-microalgae (MP-MA) aggregates. These aggregates can increase effective density, thereby altering the vertical distribution and environmental fate of both microplastics and microalgae. However, the sinking mechanisms of these aggregates are not fully understood, partly due to their irreg...

Precursor flat urothelial lesions: Molecular landscape, pathogenesis, and biological insights.

Flat urothelial lesions represent a diagnostically challenging and clinically significant spectrum in bladder pathology. Distinguishing urothelial carcinoma in situ (CIS) from precursor lesions such as dysplasia remains problematic due to overlapping morphologic features, marked interobserver variability, and unresolved questions about biological behavior and progression risk. These challenges pos...

SPECTRAL: An Intelligent and Ultra-Sensitive Photonic Hydrogel Platform for Biomarker-Based Cancer Prediction.

Point-of-care (POC) biosensing holds great promise for noninvasive cancer diagnostics, as circulating tumor DNA (ctDNA) serves as a minimally invasive...

Gliomas as network diseases: Neuron-tumor interactions, connectome disruption, and clinical implications.

BACKGROUND: Gliomas are increasingly understood as disorders of distributed brain networks rather than focal lesions confined within radiographic marg...

Tubulointerstitial Diseases: An Updated Framework for Diverse and Emerging Entities.

Tubulointerstitial diseases represent a heterogeneous group of kidney diseases with diverse causes and overlapping histopathologic and immunophenotypi...

Decoding Parkinson's progression: A multi-modal SuStaIn ensemble approach validated on real-world PPMI data.

BACKGROUND: Parkinson's disease (PD) exhibits substantial heterogeneity in clinical presentation and longitudinal progression, complicating prognosis,...

Performance of multimodal large language models for the detection and characterization of bone lesions on radiographs.

PURPOSE: Multimodal large language models (LLMs) offer emerging capabilities in medical image interpretation; however, their efficacy in orthopedic on...

Assessing the Reliability of MRI and CT Scans for Liver Volume Estimation in Patients Undergoing Liver Transplantation.

OBJECTIVE: Magnetic resonance imaging (MRI) and computed tomography (CT) are commonly used to measure organ volumes, but accuracy has not been methodi...

Instance-Aware Pseudo-Labeling and Class-Focused Contrastive Learning for Weakly Supervised Domain Adaptive Segmentation of Electron Microscopy.

Annotation-efficient segmentation of the numerous mitochondria instances from various electron microscopy (EM) images is highly valuable for biologica...

Machine learning-based integration of respiratory oscillometry and spirometry for predicting clinical outcomes in spinal muscular atrophy.

UNLABELLED: Assessing respiratory function in spinal muscular atrophy (SMA) is challenging due to the effort-dependent nature of traditional spirometr...

Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.

BACKGROUND: Telomeres, located at chromosome ends, regulate cell division and maintain genomic stability. Telomere-related genes (TRGs) play essential...

Human-to-Rat Validation of PMI Biomarkers: A Bidirectional Cross-Species Metabolomics Study Reveals Asymmetric Translation.

Accurately estimating the post-mortem interval (PMI, also known as time since death) remains a major challenge in forensic science due to substantial ...

The potential role of artificial intelligence in the diagnosis of Acanthamoeba keratitis-a scoping review.

BACKGROUND: Acanthamoeba keratitis (AK) is a severe, sight-threatening infectious disease with a rising global incidence, linked to the increasing use...

BC-SwinNet: Swin transformer and CNN with multi-objective optimization for multi-class breast cancer detection using Histopathological images.

Breast cancer remains a major global health concern and is the leading cause of cancer-related deaths among women worldwide. It is estimated that by 2...

Abstraction-dependent diagnostic performance of a multimodal foundation model in oral epithelial dysplasia.

The reliability of general-purpose multimodal large language models (LLMs) in oral histopathologic image interpretation remains incompletely character...

Differential Attention Feature Aggregator (DAFE) for Advanced Melanoma Detection.

Melanoma is a highly aggressive form of skin cancer with a significant mortality rate. Over the past two decades, its incidence has been on the rise a...

An optimized graph neural network approach for robust and explainable IoT intrusion detection against adversarial attacks.

The swift incorporation of cutting edge technologies has expanded the range for a potential adversary to conduct adaptive attacks against systems and ...

A Unified Deep Learning Framework for Instance Segmentation Across Diverse Cytological Stains.

OBJECTIVE: Assess whether a single instance-segmentation model can operate robustly across multiple cytological stains, avoiding stain-specific pipeli...

Artificial Intelligence in Breast Cancer Lymph Node Evaluation: Is Neoadjuvant Chemotherapy the Achilles' Heel?

CONTEXT.—: Artificial intelligence (AI) has demonstrated high accuracy in detecting lymph node (LN) metastases in treatment-naïve invasive breast canc...

Single-cell and bulk omics uncover fibroblast heterogeneity and HSPH1 as a key driver in Barrett's esophagus to esophageal adenocarcinoma progression.

BACKGROUND: Esophageal adenocarcinoma (EAC) is a highly aggressive malignancy with poor prognosis, often evolving from Barrett's esophagus (BE). Under...