Pathology

Artificial intelligence in microscopic hair imaging for scalp disorders: From image acquisition to clinical decisions.

Medical imaging plays a central role in modern clinical decision-making by transforming raw image data into actionable diagnostic insights. In the context of scalp and hair disorders, microscopic hair imaging has emerged as a critical tool for non-invasive, repeatable, and cost-effective evaluation. This review provides the first comprehensive and systematic overview of the application of artifici...

CRISPR-Cas12a/Cas13a in cancer molecular diagnosis.

Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is limited by its invasiveness, inability to capture tumor heterogeneity, and failure to support dynamic monitoring. Liquid biopsy has emerged as a non-invasive alternative, enabling the analysis of circulating tumor biomarkers (e.g., ctDNA, miRNAs, exo...

The Right Ventricle, the Forgotten Chamber or Not.

Right ventricular (RV) enlargement or dysfunction evaluation is the cornerstone for diagnosis, prognostications, and treatment planning in a variety o...

Nitenpyram promotes breast cancer progression via PARP1: Integration of multi-omics analyses with experimental validation.

Nitenpyram (NIT) is an insecticide used primarily for flea control in pets, especially cats and dogs. Some studies suggest that NIT is associated with...

Incremental learning approach for semantic segmentation of skin histology images.

This study presents an incremental learning framework to enhance the generalization and robustness of transformer-based deep learning models for segme...

Machine Learning-Integrated Pharmacophore, DFT Analysis, and molecular dynamics of Diosmetin as a potent ache inhibitor with neuroprotective activity in a Scopolamine-Induced alzheimer's zebrafish model.

Alzheimer's Disease (AD) is a degenerative disorder of the brain that causes a gradual loss of cognitive function. The cholinergic hypothesis suggests...

Lanthanide-Doped Organic Framework Sensor Array Coupled with Machine Learning for Minimally Invasive Glioma Diagnosis via Cerebrospinal Fluid Biopsy.

Glioblastoma multiforme (GBM), the most malignant subtype of glioma, poses significant diagnostic challenges due to limitations in current methods, su...

Enhancing Early Detection of Contralateral Breast Cancer in Breast Cancer Survivors Using AI-Assisted Mammography.

BACKGROUND: Women with a history of breast cancer face an elevated risk of developing contralateral breast cancer (CBC). Although annual mammographic ...

Clinical development of molecular residual disease (MRD) and multi-cancer early detection (MCED) using liquid biopsy multiomics with artificial intelligence (AI).

BACKGROUND: Early detection of cancer and precise recurrence monitoring remain major unmet needs in oncology. Conventional screening is limited to a f...

The effect of neoadjuvant therapy on radiological, surgical, and pathological results in nonmetastatic breast cancer: A retrospective observational study.

The aim of the study was to evaluate the concordance between radiological imaging modalities and pathological findings and to test whether neoadjuvant...

The DNA-Based Disease Diagnosis Model with Strand Displacement Reaction.

MicroRNAs (miRNAs) serve as crucial biomarkers in disease diagnosis. Although silicon-based electronic machine learning models provide efficient means...

Radiomics-based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas (ROMUS): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer (MITO) study.

OBJECTIVE: To develop machine-learning models that incorporate clinical information and radiomics features extracted from ultrasound images to disting...

Reimagining Thomas Lewis's perspective: using artificial intelligence tools to predict cardiovascular risk from computed tomography.

Artificial intelligence (AI) is reshaping cardiovascular imaging, transforming it from a set of diagnostic tests into powerful tools of precision medi...

Fragmentomic liquid biopsy enables early breast cancer detection, molecular subtyping and lymph node assessment.

Breast cancer remains a leading global health concern in women, while screening is still limited by imaging accessibility and reduced sensitivity in d...

Percutaneous nephrostomy guidance by a convolutional-neural-network-based optical coherence tomography endoscope.

Percutaneous nephrostomy is widely used in kidney access surgeries. Despite its prevalence in urological interventions, it presents two operational ch...

A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICCA) is a rare but highly lethal adenocarcinoma arising within the hepatic parenchyma. Diagnosis present...

Deep Learning-Derived Body Composition Analysis Predicts Long-Term Mortality After Transcatheter Aortic Valve Replacement.

OBJECTIVE: To examine the association between body composition metrics derived from preprocedural computed tomography (CT) angiography and all-cause m...

Artificial Intelligence-based Gram Stain Classification: Accuracy and Clinical Utility in Positive Blood Cultures.

INTRODUCTION: With the rapid advancement of artificial intelligence (AI) technology, AI has been applied to the detection of pathogens that cause infe...

Unraveling the connection between PFOA and bladder cancer: A study integrating network toxicology, molecular docking, and experimental validation.

PFOA, an environmental pollutant linked to bladder cancer, has unclear molecular mechanisms. Integrating transcriptomic data with network toxicology a...

Advances in the application of photodynamic diagnosis in Skin Tumors.

Photodynamic Diagnosis (PDD) is a non-invasive imaging technique. It relies on a photosensitizer that, when activated by a specific light source, caus...