Pathology

Latest AI and machine learning research in pathology for healthcare professionals.

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Validation of a Pretrained Artificial Intelligence Model for Pancreatic Cancer Detection on Diagnosis and Prediagnosis Computed Tomography Scans.

PURPOSE: To evaluate PANCANAI, a previously developed AI model for pancreatic cancer (PC) detection,...

Fourier ptychography microscopy for digital pathology.

Fourier ptychography microscopy (FPM) has made significant progress since its invention in 2013, tha...

CellSeg3D, Self-supervised 3D cell segmentation for fluorescence microscopy.

Understanding the complex three-dimensional structure of cells is crucial across many disciplines in...

Patient acceptability of CITOBOT for cervical cancer screening: A mixed-method study.

This study assessed the acceptability of CITOBOT, a device for early cervical cancer screening in a ...

Systematic review of generative adversarial networks (GANs) in cell microscopy: Trends, practices, and impact on image augmentation.

Cell microscopy is the main tool that allows researchers to study microorganisms and plays a key rol...

Recognition of suspended particles based on Mueller matrix microscopic imaging and deep learning.

Suspended particles are widely present in various aquatic environments, but they are difficult to de...

[Incidental pulmonary nodules on CT imaging: what to do?].

Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage)...

Fine-tuned large language model for classifying CT-guided interventional radiology reports.

BackgroundManual data curation was necessary to extract radiology reports due to the ambiguities of ...

Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.

OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, character...

Artificial Intelligence-Driven Proteomics Identifies Plasma Protein Signatures for Diagnosis and Stratification of Behçet's Disease.

The diagnosis of Behçet's disease (BD) predominantly relies on clinical symptoms, indicating an urge...

Physiological Response of Tissue-Engineered Vascular Grafts to Vasoactive Agents in an Ovine Model.

Tissue-engineered vascular grafts (TEVGs) are emerging as promising alternatives to synthetic grafts...

GPT-4o and Specialized AI in Breast Ultrasound Imaging: A comparative Study on Accuracy, Agreement, Limitations, and Diagnostic Potential.

OBJECTIVES: This study aimed to evaluate the ability of ChatGPT and Breast Ultrasound Helper, a spec...

Enabling Early Identification of Malignant Vertebral Compression Fractures via 2.5D Convolutional Neural Network Model with CT Image Analysis.

STUDY DESIGN: This study employed a retrospective data analysis approach combined with model develop...

Enhancing Lung Cancer Diagnosis: An Optimization-Driven Deep Learning Approach with CT Imaging.

Lung cancer (LC) remains a leading cause of mortality worldwide, affecting individuals across all ge...

Diagnostic Performance of Multimodal Large Language Models in the Analysis of Oral Pathology.

OBJECTIVE: This study evaluated the accuracy and repeatability of ChatGPT-4o, a multimodal AI model,...

PCPAm - A dataset of histopathological images of penile cancer for classification tasks.

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underd...

Adolescent lumbar disc herniation: etiology, diagnosis, and treatment options.

Adolescent lumbar disc herniation (ALDH) is a type of disease with a much lower incidence than adult...

Algorithm-based intraoperative diagnosis of liver tumors using infrared spectroscopy.

Liver cancer, including hepatocellular carcinoma (HCC), cholangiocellular carcinoma (CCC), and metas...

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases.

There are over 7000 rare diseases, some affecting 3500 or fewer patients in the United States. Due t...

Attention-driven UNet enhancement for accurate segmentation of bacterial spore outgrowth in microscopy images.

Analyzing microscopy images of large growing cell samples using traditional methods is a complex and...

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