Pathology

Machine learning models based on adipocyte fatty acid-binding protein help predict the chronic and lethal outcomes of patients with drug-induced liver injury.

PURPOSE: Some patients with drug-induced liver injury (DILI) would progress into chronicity or lethal. Although adipocyte fatty acid-binding protein (AFABP) is essential in liver diseases, its role in DILI is unknown. We aimed to investigate their association and construct predictive models for chronic/lethal DILI using machine learning. METHODS: DILI patients (n = 331) were enrolled and categoriz...

Regularized Single-Cell Imaging Enables Generalizable AI Models for Stain-Free Cell Viability Screening.

Cell viability assays are essential tools in biomedical research and drug development. Artificial intelligence (AI) offers the potential to simplify these assays by predicting cell viability directly from brightfield microscopy images, but current models lack generalizability across diverse cell types and treatments. Here, we introduce a strategy called "regularized imaging", where single cells ar...

HistoNeRF: An Accessible and Intelligent Approach for Comprehensive 2D-to-3D Histological Assessment.

Histological analysis is central to biomedical research and diagnostic pathology, yet conventional two-dimensional (2D) sectioning captures only limit...

Identification and Localization of Breast Tumor Components via a Convolutional Neural Network Based on High-Frequency Ultrasound Combined With Histopathologic Registration: Prospective Study.

BACKGROUND: Given the highly heterogeneous biology of breast cancer, a more effective noninvasive diagnostic tool that unravels microscopic histopatho...

Influence of personalized human head modeling and resolution on EEG source localization for rapid brain mapping.

OBJECTIVE: To evaluate the trade-offs among model resolution, anatomical fidelity, computational cost, and localization accuracy in EEG source imaging...

An annotated dataset of Gram stains from positive blood cultures.

Bloodstream infections (BSIs) of high morbidity and mortality are across all age groups, and urgent for accurate intervention. Gram stain interpretati...

Serum peptidomics by MALDI-TOF MS coupled with machine learning approaches for diagnosis of primary liver cancer.

Primary liver cancer (PLC) is one of the most common malignant tumors worldwide. Due to its insidious onset, 70 to 80% of patients are diagnosed at an...

IPATH: A Large-Scale Pathology Image-Text Dataset from Instagram for Vision-Language Model Training.

Recent advancements in artificial intelligence (AI) have revealed important patterns in pathology images imperceptible to human observers that can imp...

High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of swimming zebrafish larvae.

Understanding the behavioral and morphological dynamics of moving model organisms like the zebrafish larvae requires accurate, high-throughput 3D anal...

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a significant role in renal cell carci...

Deep learning-derived CT body composition enhances survival risk stratification beyond the TNM system in locally advanced gastric cancer: a multi-modality cohort study.

BACKGROUND: Survival outcomes in locally advanced gastric cancer remain heterogeneous despite standard treatment and outcome classifications. Visceral...

Efficiency of artificial intelligence in identifying histological tissues from microscopic images.

Histology is an essential, yet difficult, subject to study in medicine. As artificial intelligence (AI) is rapidly evolving with ever-growing image re...

Machinability and tribological optimization of origami-inspired Almond Shell-PMMA via RSM, ML, and TOPSIS.

An integrated approach combining Response Surface Methodology (RSM), Machine Learning (ML-SVM) and TOPSIS optimization method is applied in this study...

Spatial transcriptional profiling of CHB liver biopsies reveals an undetected population of zonally biased HBV-integrated cells.

BACKGROUND & AIMS: HBV covalently closed circular DNA (cccDNA) and HBV-integrated DNA (iDNA) are features of chronic HBV (CHB). Elimination of both ce...

On the transfer learning behavior of domain-specific vision-language models in screening mammography.

Vision-Language models have shown remarkable performance for natural images and text. Given the homology of the anatomy, high gray-scale image dimensi...

Radiogenomics: Current Understandings and Future Perspectives.

Radiogenomics is a rapidly developing field that links radiological image features (radiomics) to genomic-level data (genomics, transcriptomics, and e...

Cancer-Like Fragmentomic Characteristics of Somatic Variants in Cell-Free DNA.

Cell-free DNA (cfDNA) in plasma consists of short DNA fragments resulting from a non-random fragmentation process, with distinct fragmentomic characte...

Extracellular matrix stiffness drives post-mitotic nuclear pore complex assembly to promote neuroblastoma pathogenesis.

Nuclear pore complex (NPC) undergoes dynamic changes in physiology and pathology, yet its roles in neuroblastoma (NB) remain unclear. We demonstrated ...

The Future of Non-muscle-invasive Bladder Cancer: Towards a Molecular-Digital Paradigm for Personalized Management.

The management of non-muscle-invasive bladder cancer (NMIBC) is undergoing a major paradigm shift driven by molecular biomarkers, artificial intellige...

Hierarchical Cross-scale Machine Learning for Enhanced Interpretation and Prediction of Phosphorus Removal by Metal Oxides Materials.

Phosphorus pollution necessitates advanced water remediation technologies. Metal-oxide materials show significant promise but face complexity arising ...