Pathology

Interpretable Machine Learning Model Using Digitized US Features for Classifying Complex Thyroid Nodules.

Purpose To develop a digitized integrated feature-based interpretable machine learning classificatio...

A new method to measure pore radius distribution of powders.

The pore radius distribution plays a significant role in characterizing the porous structure of powd...

Prognostic Significance of Lymph Node Ratio for Overall Survival in Patients with Lymph Node-Positive Bladder Cancer Post-Radical Cystectomy and Chemotherapy: A Multicenter Cohort Analysis.

BACKGROUND: The lymph node ratio (LNR) is gaining recognition as a prognostic biomarker for various ...

Rapid, label-free cancer detection in fresh pancreatic tissue using deep learning and multispectral Mueller matrix polarimetry.

BACKGROUND: Frozen section (FS) tissue assessment is essential for guiding intraoperative surgical d...

Deep learning drives autonomous molecular reactions with single-bond selectivity in tetra-brominated porphyrins on Au(111).

The pursuit of autonomous chemical transformations with single-bond precision represents a central c...

Radiomics of Pericoronary Adipose Tissue and CT-FFR to Predict Major Adverse Cardiovascular Events in Patients with T2DM Complicated by CAD.

This study aims to integrate lesion-specific pericoronary adipose tissue (PCAT) radiomics analysis w...

Generalisation of automatic tumour segmentation in histopathological whole-slide images across multiple cancer types.

Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a g...

Foundation model cascades enable zero-shot microscopy image analysis for cell therapy manufacturing.

BACKGROUND AIMS: The scalable manufacturing of cell therapies creates a significant need for robust ...

Comparison of bulk flow measurements in the large vessels between four-dimensional flow (4D-flow) and two-dimensional phase contrast (2D-PC) magnetic resonance imaging (MRI).

AIM: The clinical integration of four-dimensional flow magnetic resonance imaging (4D-flow MRI) for ...

The critical role of standards for AI in digital pathology: Digital Pathology Association Concept Paper.

BACKGROUND: The field of pathology has not yet fully realized the potential of artificial intelligen...

Explainable Artificial Intelligence-Driven Salivary Exosome Spectroscopic Profiling for Clinical Diagnosis and Metastasis Detection of Oral Cancer.

Oral squamous cell carcinoma (OSCC), the most common oral malignancy, requires accurate diagnostic m...

Expanded Indications in Advanced Endoscopic Resection of Malignant Gastrointestinal Lesions.

PURPOSE OF REVIEW: Endoscopic resection (ER) has transformed the management of early gastrointestina...

Development and validation of an artificial intelligence-based model for diagnosing benign, borderline, and malignant adnexal masses.

Classification of benign, borderline, and malignant adnexal masses is critical to effective clinical...

Machine learning-based classification of papillary thyroid carcinoma versus multinodular goiter using preoperative laboratory and cytology data.

Integrating deep learning and radiomics for precise identification of luminal A/B breast cancer subtypes on dynamic contrast-enhanced MRI.

BACKGROUND: Accurate differentiation between luminal A and B subtypes of breast cancer is critical f...

Artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study.

BACKGROUND: Nasopharyngeal carcinoma (NPC) poses significant diagnostic challenges due to the anatom...

Development of machine learning-driven non-invasive diagnostic models for idiopathic membranous nephropathy in Chinese patients.

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a major cause of nephrotic syndrome and end-s...

IR Spectroscopy and Linear Support Vector Machine Analysis of Colorectal Liver Metastasis.

The Colorectal Liver Metastasis (CLM) library contains 756,096 full range Fourier transform infrared...

An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps.

OBJECTIVES: The aim of this study was to develop an artificial intelligence model to automatically d...

Identification of a potential relationship between pigmented villonodular synovitis and atherosclerosis using comprehensive bioinformatics analyses.

BACKGROUND: This study investigates the pathogenesis of Pigmented Villonodular Synovitis (PVNS) usin...

Exploration of the Application of Multimodal Feature Analysis Based on Random Forest Algorithm Combining Ultrasound Elastography and Contrast-Enhanced Ultrasound in the Diagnosis of Ovarian Tumors.

OBJECTIVE: This study aimed to build a multimodal ultrasound (color Doppler flow imaging/shear wave ...