Pathology

Deep Learning for Differentiating Benign From Malignant Bile Duct Dilation on MRCP: Development and Prospective Evaluation of an Xception-Logistic Regression Ensemble Model.

BACKGROUND: Accurate identification of benign and malignant bile duct dilatation (BDD) is needed to determine its management plan. Conventional imaging evaluation is subjective, whereas deep learning (DL) offers potential for automated objective assessment. PURPOSE: To construct and evaluate DL models and ensemble strategies based on magnetic resonance cholangiopancreatography (MRCP) images for id...

Emerging biomarkers in prostate cancer diagnosis and treatment: Insights into genetic, RNA and metabolic markers (Review).

Prostate cancer remains one of the most prevalent malignancies and a major cause of cancer‑related mortality among men worldwide. Despite widespread use of prostate‑specific antigen testing, current diagnostic approaches suffer from low specificity and limited ability to distinguish between indolent and aggressive disease, resulting in overdiagnosis and overtreatment. Advances in molecular biology...

Unraveling the microbiome's role in breast cancer progression and treatment response.

The human microbiome, encompassing microbial communities in the gut and breast tissue, has emerged as a critical modulator of breast cancer (BC) initi...

A comparative study of computer vision models for oral cancer detection from oral photographs.

BACKGROUND AND OBJECTIVE: Early detection of oral cavity cancers is critical for improving patient survival rates and treatment efficacy. In this cont...

Artificial intelligence and multi-omics integration in liquid biopsy for genitourinary cancers: a systematic scoping review.

BACKGROUND: Liquid biopsy, combined with multi-omics profiling and artificial intelligence (AI), offers a minimally invasive strategy for cancer detec...

Non-invasive diagnosis of metabolic dysfunction-associated steatotic liver disease: Current status, challenges, and future directions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent liver disease globally and a significant public health challeng...

Morphologic Evaluation of Hyperchromatic Crowded Groups Present in Cervical Thin Prep Cytology Tests as Identified by the Hologic Genius Digital Diagnostics System: A Descriptive Study.

BACKGROUND: Our descriptive study focused on morphologic characteristics of hyperchromatic crowded groups (HCGs) in ThinPrep cervical cytology tests w...

Machine Learning for Classification in Lung Cancer Using Routine Clinical and Laboratory Data.

BACKGROUND: Accurate pathological classification of lung cancer is essential for informing treatment strategies. However, invasive biopsy procedures a...

Cross-modality fusion of hematology-based digital and molecular biomarkers for intelligent epidemiological screening and surveillance of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains a critical challenge due to the disease's complexity and the limitations of current screenin...

From macroscopic clearance to molecular eradication: paradigm shift and future perspectives in the detecting of residual lesions after transurethral resection of bladder tumors.

INTRODUCTION: Residual lesions after transurethral resection of bladder tumor (TURBT) are a major contributor to recurrence in bladder cancer. Advance...

Longitudinal Study of Macular Preservation and Geographic Atrophy Progression in Age-Related Eye Disease Study 2.

PURPOSE: To investigate the natural history of macular tissue preservation in geographic atrophy (GA) by evaluating the relationship between the macul...

Machine learning-assisted photoelectrochemical biosensor based on DNA-AgNCs nanowires for exosomal lncRNA intelligent diagnosis.

BACKGROUND: Exosomal long non-coding RNA (lncRNA) as a burgeoning biomarker, its abnormal expression is closely related to the progression of cancer. ...

Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview.

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinical heterogeneity. Traditional single-analyte bi...

Unveiling CDKN1A and RELA: Machine learning-driven aging biomarkers for precision diagnosis and therapy in knee osteoarthritis.

BACKGROUND: Knee Osteoarthritis (KOA) is a degenerative joint disease marked by progressive cartilage deterioration, closely tied to cellular senescen...

Artificial Intelligence and Machine Learning in Health Care: Current Capabilities, Emerging Potential, and Future Directions.

This article reviews how artificial intelligence and machine learning are reshaping health care. After a historical overview and glossary, we explore ...

Expansion omics: from expansion microscopy to spatial omics.

Tissue expansion, originally developed for super-resolution imaging, has become a foundation for expansion omics (ExO), a growing field that uses phys...

Development of a machine learning model for preoperative prediction of spread through air spaces in resectable non-small cell lung cancer: A single-center retrospective study.

Spread through air spaces (STAS) is a pathological feature associated with poor prognosis in non-small cell lung cancer (NSCLC). However, its diagnosi...

The role of artificial intelligence in advancing urologic care: From diagnostics to therapeutics.

Artificial intelligence (AI) is gradually altering urology by improving diagnostic precision, prognostic evaluation, and therapy decisions in a broad ...

[Digital, DICOM, diagnostics-unity over chaos : Data communication in digital pathology].

Digitization of histological specimens enables new computer-assisted analysis and artificial intelligence (AI)-supported diagnostics, but is hampered ...

Forensic geolocation of Norwegian soil samples using random forest analysis of microbiomes.

Soil is a substrate easily picked up during everyday activities due to its ubiquity and adhesiveness. A method to determine the origin of soil precise...