Pathology

From conventional screening to self-driving discovery: Organ-on-Chip platforms as engines for AI-guided nanomedicine.

Nanoparticles have become an essential platform for next-generation drug delivery and therapeutic development, yet clinical translation remains limited by an incomplete understanding of their interactions within human biological systems. Organ-on-a-chip technology offers a powerful approach to evaluate efficacy and safety of nanomedicine under physiologically relevant conditions in human cells by ...

Integrative bioinformatics and machine learning combined with experimental validation in a doxorubicin-induced model identify BACH2, NXPH4, CD1E, and LIF as sodium overload-related molecular signatures in dilated cardiomyopathy.

INTRODUCTION: Dilated cardiomyopathy (DCM) is a leading cause of heart failure and remains a major clinical challenge due to its complex etiology and lack of effective targeted therapies. Sodium overload-induced necrosis, a recently described form of regulated cell death, has emerged as a novel contributor to cardiovascular injury, but its role in DCM remains poorly defined. AIMS: This study aimed...

EASDnet: Empowering human-centered evidence-based medicine through an evidence and attention-based spatial disparity network for discriminative colorectal cancer histopathological screening and attribution.

PURPOSE: Accurate preoperative staging of colorectal cancer is critical to guide treatment decisions, including eligibility for R0 resection, to reduc...

Salvianolic acid C attenuates liver fibrosis and inhibites hepatic stellate cell activation by targeting FAP/TβRI/SMAD axis.

BACKGROUND: Liver fibrosis remains a major clinical challenge with limited effective therapeutic options. Salvianolic acid C (SAC), a major water-solu...

Subcutaneous tissue structural feature identification using unsupervised machine learning.

Accurate quantification of the structural features of subcutaneous (SC) tissue is essential for understanding its physiology and developing predictive...

Vascularisation in 3D bioprinted models: emerging solutions engineering functional tissues and tumour models.

Three-dimensional (3D) bioprinting enables the fabrication of tissues with controlled architecture and cell composition, yet the formation of mature a...

An AI-based IHC quantification technique for assisting in the differentiation of MCL from CLL/SLL.

This study explores the application of artificial intelligence technology for the quantitative analysis of immunohistochemical markers to differentiat...

Deep Learning on Histology Images for Differentiating Fibro-osseous Lesions of the Jaw.

Fibrous dysplasia (FD), cemento-ossifying fibroma (COF), and cemento-osseous dysplasia (COD) are fibro-osseous lesions of the jaw that share histologi...

Predicting Plaque Vulnerability Using Machine Learning-Enabled Nanoagents Sensitized Molecular High-Resolution Magnetic Resonance Imaging Data.

Molecular imaging based on paramagnetic nanoagents has emerged as an intriguing strategy to sensitize the local magnetic properties of pivotal patholo...

Distinction between primary and metastatic mucinous ovarian carcinoma from histopathology images using deep learning.

Accurately distinguishing between primary and gastrointestinal metastatic mucinous ovarian carcinoma (MOC) is crucial but remains highly challenging. ...

Automated Melanocytic Lesion Classification: Capsule Networks Trained With Synthetic Images Can Outperform Networks Trained With Real Images.

BACKGROUND/OBJECTIVES: Convolutional neural networks (CNNs) are known, due to inherent flaws in their design, to be subject to classification error. M...

Computational Fluid Dynamics Simulations to Inform Cancer Therapeutics.

Cancer therapies such as chemotherapy, radiopharmaceutical therapy, and transarterial embolization rely on effective drug or radiation delivery throug...

An optimized hierarchical attention assisted deep learning model for brain tissue classification.

BACKGROUND & OBJECTIVE: Precise differentiation of brain tissue from Magnetic Resonance Imaging is a vital constraint in various medical applications....

Dual selective gleason pattern-aware multiple instance learning with uncertainty regularization for grade group prediction in histopathology images.

Accurate prediction of Gleason Grade Group (GG) is of great importance for prostate cancer risk stratification and treatment planning. Although multip...

Automatic Nanoparticles Counting for TEM Images by Combination of Distance Transform, Watershed Segmentation and U-Net Machine Learning.

Accurate counting of nanoparticles in microscopy images such as SEM and TEM is critical for advancing materials science and nanotechnology. Though man...

Comparative Evaluation of Transfer Learning Models for Detecting Malignant Cells in Urinary Cytology.

AIMS AND OBJECTIVES: In the present paper, we compared the efficiency of six transfer learning models to detect malignant cells in urine cytology. We ...

End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study.

BACKGROUND: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet ...

Artificial intelligence as a diagnostic support tool in hysteroscopy: current evidence and clinical implications.

BACKGROUND: Hysteroscopy allows direct inspection of the uterine cavity for many conditions. Despite being widely adopted, its diagnostic accuracy lar...

Assessing Artificial Intelligence in Breast Imaging: A Survey of Breast Radiologists' Insights on Adoption, Benefits, and Challenges.

OBJECTIVE: To evaluate radiologists' opinions on the clinical applications of artificial intelligence (AI), especially AI-based computer-aided detecti...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS score genes has limited efficacy in differentiati...