Pathology

A Triage Model for HR-HPV Positive Women Based on Methylation of Human and HPV Genes.

The aim of this study is to develop a machine learning triage model for HR-HPV positive women based on methylation patterns of human and HPV genes to predict the risk of CIN2 +, and to compare its performance with traditional detection techniques. A total of 512 eligible women participated in the study, with exfoliated cervical cell specimens collected for methylation analysis of both human and HP...

Cross-attention multimodal fusion for EGFR mutation prediction: A predictive model using CT and whole-slide images.

BACKGROUND: The prediction of Epidermal Growth Factor Receptor (EGFR) mutation status in advanced lung adenocarcinoma is crucial for targeted therapy. Since EGFR mutations manifest as both macroscopic imaging features on CT and microscopic morphological changes in tissue, integrating these multiscale signals is essential for a comprehensive diagnostic assessment. However, current related research ...

A CT-based deep learning model to differentiate between benign and malignant adrenal lesions.

OBJECTIVE: To develop a deep learning model to differentiate benign from malignant adrenal lesions. MATERIALS AND METHODS: A total of 380 patients wit...

Accelerating the implementation of digital pathology in India.

Digital pathology (DP), which utilizes whole-slide imaging (WSI), adds value to traditional pathology by enabling high-resolution imaging, remote diag...

Integrated plasma proteomics and metabolomics reveal immunometabolic pathways and predictive signatures for age-related eye diseases.

BACKGROUND AND AIMS: Age-related eye diseases (AREDs) share aging as a major risk factor, but the systemic molecular changes preceding disease onset r...

Invisible Signals, Visible Dilemmas: The Ethical Frontiers of Liquid Biopsy in Precision Oncology.

This critical review synthesizes the ethical, technical, and equity dilemmas emerging from the rapid clinical translation of liquid biopsy technologie...

Artificial intelligence-driven early screening and diagnosis of pancreatic cancer: technical innovations, clinical applications, and precision medicine strategies.

BACKGROUND: Pancreatic cancer is characterized by prolonged subclinical progression, molecular heterogeneity, and late clinical presentation, resultin...

Machine learning-enhanced plasma proteomics discriminates pancreatic cancer-associated diabetes from type 2 diabetes mellitus.

Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type...

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature...

Malignant Transformation Risk in Patients With Oral Leukoplakia and Type 2 Diabetes Mellitus.

INTRODUCTION AND AIMS: Oral leukoplakia (OLK) is the most common oral potentially malignant disorder, with a malignant transformation rate of up to 9....

Peripheral blood mononuclear cell DNA methylation signatures guide surgical decision-making in indeterminate pulmonary nodules.

BACKGROUND: Distinguishing malignant from benign pulmonary nodules remained a significant clinical challenge. Given the involvement of DNA methylation...

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment.

Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adolescents. Imaging plays a central role from diagnosi...

Integration of Single-Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma.

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular imm...

Identification and Screening of Lactate-Related Genes as Molecular Markers for Early Diagnosis of Steroid-Induced Osteonecrosis of the Femoral Head.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a major cause of disability among young and middle-aged adults. However, current diagnosi...

The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases - Between Potential and Real Clinical Support.

INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associated malignancy characterized by destructive tumors i...

Towards scalable deep learning for automated microscopy in harmful algal bloom monitoring: Data-centric workflow and multi-region generalisation.

Harmful algal blooms (HABs) pose growing risks to drinking-water supplies and ecosystems, yet routine monitoring remains dependent on manual light mic...

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging.

Ultrasound microvascular imaging (UMI) has emerged as a powerful, noninvasive modality for visualizing the microvasculature, offering valuable insight...

Use of the Ion Robot in the Diagnosis of Pulmonary Nodules: Fine Needle Aspiration Versus Cryobiopsy.

BACKGROUND: Robotic-assisted bronchoscopy platforms provide an innovative approach to the sampling of pulmonary nodules. As compared to other technolo...

Hybrid learning/numerical framework for fast and robust electric field simulation in irreversible electroporation.

OBJECTIVE: Irreversible electroporation (IRE) represents a promising non-thermal ablation modality for the treatment of deep-seated tumors. However, i...

Unlocking biodiversity data with robotic imaging and AI-driven transcription of natural history collections.

Digitizing metadata on natural history specimen labels remains a critical bottleneck for biodiversity research. We present a transformative workflow i...