Pathology

Deep learning model for pathological invasiveness prediction using smartphone-based surgical resection images in clinical stage IA lung adenocarcinoma (SuRImage): a prospective, multicentric, diagnostic study.

BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segmentectomy and lobectomy. Frozen section analysis is time consuming and not always reliable for LUAD diagnosis and grading. We developed deep learning models using surgical resection images to assist in prompt diagnosis and risk stratification of stage...

Higher Diagnostic Accuracy of an AI Model for Colposcopy Compared With Conventional and Digital Colposcopic Evaluation.

OBJECTIVE: Colposcopy involves subjective visual assessment of cervical features that may indicate cervical dysplasia. Pattern recognition during colposcopy could be enhanced by artificial intelligence (AI). Using colposcopy images with precisely mapped multiple biopsy sites and corresponding histologic diagnoses, we developed an AI model, Cervix-AID-Net, to classify colposcopy images into low-gra...

Deep Learning Empowered Microstructure Codebook: New Paradigm for Multi-Parameter Tissue Characterization Estimation.

Diffusion MRI (dMRI) enables the examination of microstructural profiles and tissue changes using specific microstructural modeling, but it requires l...

Artificial intelligence in nongynecologic cytology: A systematic review of current research and commercial tools.

BACKGROUND: Nongynecologic (non-GYN) cytology plays an important role in cellular and molecular cancer diagnosis, although its use is limited by varia...

Multicentre Evaluation of an AI-Assisted Urine Test for Clinically Significant Prostate Cancer in Men Undergoing Initial Biopsy.

The Extracellular Vesicles Gene-based Prostate Score (EGPS), powered by DeepSeek, is an artificial intelligence (AI) diagnostic tool that enhances the...

A deep learning model for histopathological diagnosis of actinic keratosis: a diagnostic case control accuracy study.

BACKGROUND: Actinic keratosis (AK) is a precancerous skin lesion with the potential to progress into squamous cell carcinoma (SCC), with an overall pr...

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application o...

NR3C1 Modulates Wnt Signalling to Influence the Invasiveness and Immune Features of Nonfunctioning Invasive Pituitary Adenomas.

Pituitary adenomas (PAs) are common intracranial tumours, and invasiveness in nonfunctioning invasive pituitary adenomas (NIPAs) predicts poor prognos...

Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.

Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...

SKOOTS: Skeleton-Oriented Object Segmentation for Mitochondria in High-Resolution Cochlear EM Datasets.

Segmenting individual instances of mitochondria from imaging datasets can provide rich quantitative information, but manual segmentation is prohibitiv...

Crashworthiness and technoeconomic assessment of bioinspired GFRP PP tubes using experiments numerical modeling and artificial neural networks.

This study presents a comprehensive experimental and computational investigation of the quasi-static axial compression behavior of glass fiber-reinfor...

A deep joint-learning proteomics model for diagnosis of six conditions associated with dementia.

Co-pathology is a common feature of neurodegenerative diseases that complicates diagnosis, treatment and clinical management. However, sensitive, spec...

A Multitask Deep Learning Approach for Tumor Segmentation and Morphological Quantification in Acral Melanoma Whole-Slide Images.

This study presents an integrated multitask deep learning framework for the automated analysis of acral melanoma from whole-slide images (WSIs). We co...

Single-Cell Sequencing and Transcriptomic Sequencing Exploration of the Mechanisms Governing Lactylation in Mitochondrial Diseases.

Mitochondrial diseases (MDs) consist of a heterogeneous spectrum of disorders resulting from mutations in either nuclear or mitochondrial DNA, disrupt...

Recent advances in corneal specular microscopy image analysis through artificial intelligence.

Although conventional automated analysis of corneal specular microscopy images has historically been limited by reproducibility challenges in the pres...

Inflammatory-nutritional biomarker scores and risk of malignant effusion in a pan-cancer cohort of 68,916 patients: Nonlinear associations and machine learning validation.

PURPOSE: Inflammatory-nutritional biomarker scores derived from routine blood tests have established prognostic value in cancer, yet their association...

High-accuracy instance segmentation of cellular structures in head and neck squamous cell carcinoma histopathology using a cyto R-CNN deep learning framework.

This study develops a deep learning-based model to automate the instance segmentation of nuclei and whole cells in hematoxylin and eosin-stained head ...

Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that carry nucleic acids, proteins, metabolites, and lipids. Their omics profiles...

Transformer-based super-resolution lung CT images improve visualization of multiple diseases.

OBJECTIVES: To assess the Transformer-based Swin2SR model for super-resolution (SR) enhancement of lung CT images and its clinical potential. METHODS:...

Developing and validating ultrasound-based machine-learning models incorporating radiomics features to predict malignancy in adnexal masses.

OBJECTIVE: The primary aim of this study was to develop and internally validate ultrasound-based radiomics models to discriminate between all types of...