Pathology

CT-based subregional and peritumoral radiomics for predicting pathological T stage of clear cell renal cell carcinoma: an exploratory study of biological mechanisms.

OBJECTIVES: To evaluate intratumoral subregional and peritumoral radiomics for predicting pathological T stage of clear cell renal cell carcinoma (ccRCC), and investigate the biological mechanisms of radiomics. MATERIALS AND METHODS: This retrospective study included 323 ccRCC patients from two centers, divided into training (n = 148), internal test (n = 38), and external validation (n = 137) sets...

Digital pathology-based artificial intelligence algorithms in prostate cancer: inside the 'black box'.

Artificial intelligence (AI) algorithms leveraging digital pathology slides are currently transforming the way urological cancers are diagnosed and graded, and they add additional prognostic, predictive and molecular subtyping information beyond traditional pathological risk stratification. This review explores recent advances in histopathology-based AI systems for prostate cancer. We examine how ...

Utilisation of intramuscular and intermuscular fat to develop a new skeletal muscle grading score which can predict treatment outcomes for locally advanced rectal cancer.

BACKGROUND: Sarcopenia has been widely studied in rectal cancer with increasing evidence to suggest that other body composition parameters, in particu...

Breathomics Analysis for Early Diagnosis of Lung Cancer Based on PTR-TOF MS: A Large Sample Size Cross-Sectional Study.

INTRODUCTION: Lung cancer remains a leading cause of cancer mortality globally, emphasising the critical need for non-invasive and cost-effective earl...

Risk prediction for chronic atrophic gastritis using a random forest model: A multicenter study.

BACKGROUND: Chronic atrophic gastritis (CAG) is a significant precancerous condition of gastric cancer (GC). CAG often lacks typical symptoms in its e...

Dental Students' Knowledge, Attitudes and Perceptions of Artificial Intelligence Tools to Aid in the Diagnosis of Oral Cancer and Oral Potentially Malignant Disorders.

BACKGROUND: Artificial intelligence (AI) has emerged as a promising tool in dentistry, particularly in the early detection of oral cancer (OC) and ora...

Toward Timely Diagnosis of Pancreatic Cancer: Revolutionizing Early Detection Through Genomics, Artificial Intelligence, and Noninvasive Biomarkers.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive cancers, typically diagnosed at an advanced stage due to its su...

Multimodal hybrid mamba classification model for tumor pathological grade prediction using magnetic resonance images.

Malignant tumors present a significant global health challenge, and accurate pathological grading is essential for personalized treatment. Traditional...

H-DCA Net: Hierarchical dual-branch coordinate attention framework for multi-scale gastric histopathology diagnosis.

BACKGROUND AND OBJECTIVE: Early and accurate diagnosis of gastric cancer is crucial for improving patient prognosis. However, conventional histopathol...

Deep learning for histopathological diagnosis of esophageal squamous cell carcinoma in biopsies: A multicenter analysis.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a major cause of cancer mortality in Asia, where histopathological diagnosis of endoscopic bi...

Kinic index: an artificial intelligence-driven predictive model and multitarget drug discovery framework for hepatocellular carcinoma patients.

Hepatocellular carcinoma (HCC) remains a major global health challenge due to its molecular heterogeneity, late diagnosis, and limited therapeutic opt...

An interpretable machine learning model for preoperative prediction of aldosterone secretion and CYP11B2 status of adrenal gland.

BACKGROUND: To investigate whether a machine learning (ML) model integrating CT-based radiomics and clinical features can noninvasively evaluate the a...

Interpretable habitat and peritumoral radiomics from multiparametric MRI for preoperative high-risk prostate cancer prediction: a multi-institutional study.

BACKGROUND: Current preoperative assessment faces limitations, including PI-RADS scoring subjectivity and diagnostic uncertainty in distinguishing hig...

Label-Free rapid bone biomarkers assessment via physics-guided machine learning-assisted photoacoustic correlation spectra analysis.

Obtaining information on bone metabolism through intraoperative or non-invasive examination remains a challenge in medical practice. Photoacoustic (PA...

Electrochemical biosensors for Calreticulin in lung Cancer.

Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers. Of t...

Detection of prostate cancer in 3D pathology datasets via generative immunolabeling.

Recent advancements in nondestructive 3D pathology offer a complement to standard histology by enabling comprehensive volumetric analyses of intact cl...

Minor salivary gland biopsy in Sjogren's disease: a diagnostic and prognostic tool toward precision medicine.

Minor salivary gland biopsy occupies a distinctive position in the evaluation of Sjögren disease (SjD), offering diagnostic and prognostic insights th...

Multifunctional biosensors redefining liquid biopsy: advancing simultaneous multianalyte detection.

Liquid biopsy has revolutionized noninvasive disease diagnosis and monitoring by detecting circulating biomarkers such as tumor-derived DNA, miRNAs, p...

Automatic Detection of Subcellular-Scale Metabolic Dynamics via Spontaneous-Stimulated Raman Spatial Colocalization.

Cellular structural heterogeneity and low intrinsic contrast in label-free bright-field imaging hinder accurate localization of subcellular structures...

Anatomy-guided visual prompt tuning for cross-modal breast cancer understanding.

Early and reliable detection of breast cancer across imaging modalities remains a long-standing challenge due to the heterogeneous appearance of lesio...