Pathology

Identification of Gene Signatures Differentiating Cancer from Normal Tissues Across Histological Classifications of Gastric Adenocarcinoma via Machine Learning Methods.

Gastric adenocarcinoma is a significant global health concern. Among the myriad histologic classification methods for this cancer, the Lauren classification stands out as a pivotal tool. Nonetheless, the precision and detail of current histological staging techniques frequently face scrutiny. Utilizing high-resolution single-cell transcriptomic data, this research delves into the distinctive gene ...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key biomarker for assessing the risk of gastric cancer. Histological classification into complete and incomplete types, along with the Operative Link on Gastric Intestinal Metaplasia (OLGIM), provides valuable prognostic information, with stage III-IV strongly associated with cancer development. Therefore,...

M2PL-GAN: Multi-View Multi-Level Pathology Semantic Perception Learning for H&E-to-IHC Virtual Staining.

Immunohistochemistry (IHC) staining is crucial for determining tumor subtypes, obtaining protein expression information, and developing personalized t...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical awareness, improved imaging, and revised classifica...

CMAF-Net: cross-modal attention fusion with information-theoretic regularization for imbalanced breast cancer histopathology.

Breast cancer diagnosis from histopathology images remains challenging due to two intertwined factors: severe class imbalance, where malignant cases r...

A Review on Image Processing and Fractal Analysis in Oral Potentially Malignant Disorders.

AIM: The clinical evaluation of patients with oral potentially malignant disorders is primarily based on physical examination and observable clinical ...

Ryanodine receptor 2 mutations in catecholaminergic polymorphic ventricular tachycardia: From molecular mechanisms to precision medicine.

Catecholaminergic polymorphic ventricular tachycardia is a classic example of the successful transfer of genetic cardiology from gene discovery to imp...

Machine learning methods to evaluate fluctuation in oxygenation and peripheral tissue temperature, in sacral and trochanteric area under pressure in healthy subjects and institutionalized patients. A prospective non-randomized trial.

AIM: To evaluate the longitudinal changes observed over a period of 120 min in patterns of tissue perfusion, peripheral oxygenation and local temperat...

Hydrodynamic modulation of microplastic bioaccumulation in edible fish: Integrating biomarker networks, machine learning, and food safety perspectives.

Microplastic (MP) pollution poses increasing environmental and food safety risks, yet the role of hydrodynamics in MPs bioaccumulation and fish physio...

What practicing pathologists and oncologists should know about the new computational pathology-based companion diagnostic tools.

The integration of artificial intelligence into pathology is transforming the assessment of histological and immunohistochemical (IHC) slides, offerin...

Comment on "Artificial Intelligence for predicting post-excision recurrence and malignant progression in oral potentially malignant disorders: a retrospective cohort study".

Phosphoenolpyruvate carboxykinase 2 as a prognostic biomarker: expression and clinical significance in Group 3 and Group 4 medulloblastoma.

PURPOSE: Despite Phosphoenolpyruvate carboxykinase 2 (PCK2) has attracted growing attention as a potential biomarker in cancer research, its role in m...

The problem with the 'truth': rethinking ground truth for artificial intelligence in endometriosis diagnosis.

Artificial intelligence (AI) is revolutionizing how we practice medicine. In areas where we have traditionally struggled, such as diagnosing endometri...

PAST, PRESENT and FUTURE OF LUPUS NEPHRITIS.

INTRODUCTION: Our objective is to delineate the evolution of lupus nephritis (LN) histological classifications and management, from their origins to t...

Integrative machine learning and molecular docking reveal Narirutin targets ABCC1/ABCG2 for immune microenvironment remodeling in colorectal cancer.

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers worldwide, with late-stage diagnosis often associated with poor prognosis. The...

INHBA: a mitochondrial-related pan-cell death gene associated with the prognosis and immunity of OSCC.

Oral squamous cell carcinoma (OSCC) is a malignant tumor characterized by both clinical and molecular heterogeneity. Its rising global incidence and m...

Leveraging infarct topography for early warning: a robust model for predicting malignant cerebral edema after endovascular treatment in acute ischemic stroke.

BACKGROUND: The early prediction of malignant cerebral edema (MCE) following endovascular therapy for acute ischemic stroke is of paramount importance...

TRKB-based signature identifies high-risk squamous cell carcinoma cases and TRKB blockade reprograms tumor and stromal cells toward suppressive phenotypes.

BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) is a common age-related cancer, with a subset prone to recurrence and metastasis. Currently, no u...

Human versus artificial intelligence in oral pathology diagnosis: a comparative study of ChatGPT, Grok, and MANUS.

Artificial intelligence (AI) integration in diagnostic medicine has advanced accuracy and efficiency, particularly in pathology. This study assessed t...

Inference of drowning sites of cases in the Pearl river based on microbial community profiling and random forest algorithm.

Accurate inference of drowning sites remains a critical challenge in forensic investigations, particularly for corpses recovered from dynamic aquatic ...