Pathology

High-Precision Intelligent Diagnosis of Pancreatic Cancer: Flowing Diffuseness from Single to Whole.

Raman spectroscopy, as a label-free optical technique, provides a unique solution for tissue diagnosis. However, due to the limitation of point-by-point acquisition mode and multivariate statistical analysis methods, conventional methods pose a major bottleneck toward achieving highly time-efficient, accurate, and holistic diagnosis. Here, the authors establish line-scan Raman spectrochemical holi...

Enhancing detection and monitoring of circulating tumor cells: Integrative approaches in liquid biopsy advances.

Liquid biopsy offers a minimally invasive method for detecting and monitoring cancer, with key biomarkers including circulating tumor cells (CTCs), cell-free DNA (cfDNA), and extracellular vesicles (EVs). Among these, CTCs provide dynamic insights into tumor heterogeneity, metastatic potential, and therapeutic resistance through molecular profiling and single-cell analysis. This review examines re...

Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.

BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This stu...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-m...

Mexican dataset of digital mammograms (MEXBreast) with suspicious clusters of microcalcifications.

Breast cancer is one of the most prevalent cancers affecting women worldwide. Early detection and treatment are crucial in significantly reducing mort...

Improving internet of vehicles research: A systematic preprocessing framework for the VeReMi dataset.

The Vehicular Reference Misbehavior Dataset (VeReMi) is a vital resource for advancing Intelligent Transportation Systems (ITS) and the Internet of Ve...

Construction of a Multimodal Machine Learning Model for Papillary Thyroid Carcinoma Based on Pathomics and Ultrasound Radiomics Dataset.

The use of machine learning to integrate and analyse multimodal information has broad prospects for enhancing the precision of tumour diagnosis. Our s...

Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.

The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficulties when making clinical decisions. This study ai...

Automatic smart brain tumor classification and prediction system using deep learning.

A brain tumor is a serious medical condition characterized by the abnormal growth of cells within the brain. It can cause a range of symptoms, includi...

Deep learning for malignant lymph node segmentation and detection: a review.

Radiation therapy remains a cornerstone in the treatment of cancer, with the delineation of Organs at Risk (OARs), tumors, and malignant lymph nodes p...

Integrating attention networks into a hybrid model for HER2 status prediction in breast cancer.

Breast cancer is one of the most prevalent cancers amongst women, caused by uncontrolled cell growth in breast tissue. Human Epidermal growth factor R...

Peritoneal cytology predicting distant metastasis in uterine carcinosarcoma: machine learning model development and validation.

OBJECTIVE: This study develops and validates a machine learning model using peritoneal cytology to predict distant metastasis in uterine carcinosarcom...

Diagnostic Adjuncts and Biopsy Techniques for Oral Potentially Malignant Disorders and Oral Cavity Squamous Cell Carcinoma.

Diagnostic adjuncts for oral potentially malignant disorders such as leukoplakia or erythroplakia can aid the clinician in triaging abnormal lesions a...

Circulating miRNAs in genitourinary cancer: pioneering advances in early detection and diagnosis.

MicroRNAs (miRNAs) are noncoding, single-stranded RNAs molecules modulating gene expression thanks to their ability to bind mRNAs. Indeed, they regula...

Artificial intelligence based vision transformer application for grading histopathological images of oral epithelial dysplasia: a step towards AI-driven diagnosis.

BACKGROUND: This study aimed to classify dysplastic and healthy oral epithelial histopathological images, according to WHO and binary grading systems,...

Breast Pathology Through the Digital Lens.

Digital pathology (DP) has significantly transformed breast pathology at Mount Sinai Hospital by enhancing diagnostic accuracy, collaboration, and edu...

Breast tumour classification in DCE-MRI via cross-attention and discriminant correlation analysis enhanced feature fusion.

AIM: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be highly sensitive in diagnosing breast tumours, due to the kinetic...

Multimodal representations of transfer learning with snake optimization algorithm on bone marrow cell classification using biomedical histopathological images.

Bone marrow (BM) plays a crucial role in the hematopoietic process, producing all of the body's blood cells and maintaining the overall immune and hea...

A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.

Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social commu...

Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging.

Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection...