Pathology

A fatty acid metabolism-based deep learning model predicts biochemical recurrence and identifies NUDT19 as a candidate metabolic factor in prostate cancer.

PURPOSE: To develop a fatty acid metabolism-based deep learning model for predicting biochemical recurrence (BCR) in prostate cancer (PCa) and to identify recurrence-associated metabolic regulators. METHODS: Transcriptomic data from TCGA and GEO GSE70769 were integrated to identify fatty acid metabolism-related genes and construct a deep learning model for BCR prediction. Tumor-infiltrating lympho...

Development and validation of an interpretable ultrasound radiomics model for benign and malignant classification of breast lesions: a multicenter large-sample study.

OBJECTIVES: To develop and validate a combined ultrasound-based radiomics-clinical model for differentiating benign and malignant breast lesions. MATERIALS AND METHODS: A total of 3142 patients from eight hospitals between February 2012 and September 2024 were included in this multicenter retrospective development and validation study, with an additional single-center prospective test cohort. Lesi...

MLMarker: a machine learning framework for tissue inference and biomarker discovery.

MLMarker is a machine learning tool that computes continuous tissue similarity scores for proteomics data, addressing the challenge of interpreting co...

ACOT9, a mitochondrial metabolism-related gene, promotes ROS-associated epithelial remodeling in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is characterized by mitochondrial metabolic reprogramming, but its prognostic significance and un...

Early risk prediction in endometrial cancer using biomarker and machine learning models: a systematic review and meta-analysis protocol.

BACKGROUND: Globally, endometrial cancer (EC) is among the most prevalent gynaecological cancers, with rising incidence driven by demographic and meta...

Benchmarking of AI and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation on Screening CT: The LUNA25 Challenge.

Purpose To compare the performance of an artificial intelligence (AI) system with that of radiologists for estimating malignancy risk of indeterminate...

High-fidelity super-resolution CT radiomics for non-invasive EGFR mutation prediction in lung adenocarcinoma: a multi-center pooled analysis.

OBJECTIVE: To develop and validate a high-fidelity super-resolution (SR)-enhanced radiomics framework using a Residual Channel Attention Network (RCAN...

Performance of multimodal Large Language Models in misdiagnosed dermatologic cases: a pilot study on diagnostic accuracy and human error replication.

BACKGROUND: Multimodal Large Language Models (LLMs) are increasingly positioned as diagnostic assistants in dermatology. However, current research oft...

Human donor liver viability evaluation with polarization-sensitive optical coherence tomography.

Human liver transplantation is constrained by a critical shortage of viable donor livers. In response to this shortage, marginal livers from extended ...

Decoding fibrosis: Transcriptomic and clinical insights via AI-derived collagen deposition phenotypes in MASLD.

Histological assessment is foundational to multi-omics studies of liver disease, yet conventional fibrosis staging lacks resolution, and quantitative ...

Advances in the management of pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs), the most common CNS tumors in children, are increasingly recognized as chronic diseases with prolonged courses an...

Topology-Aware Segmentation for Tubular Structure in 3D Microscopy.

High-resolution 3D microscopy has become a foundational tool in biomedical research by reconstructing vascular and neural networks from subcellular to...

Annexin A2 as a Therapeutic Target of Artemisiae Scopariae Herba-derived Quercetin in Preventing Malignant Progression from Primary Sclerosing Cholangitis to Cholangiocarcinoma: An Integrative Study.

ETHNOPHARMACOLOGICAL RELEVANCE: Artemisiae Scopariae Herba (ASH) is traditionally used to treat cholestatic liver diseases and exhibits anti-tumour po...

Inflammation-mediated diabetes-liver disease cross-organ crosstalk: From molecular mechanisms to precision therapeutic strategies.

The rising global prevalence of diabetes mellitus and its liver complications presents a significant public health challenge. Inflammation-driven cros...

Beyond the Cuff: Deep Learning-Based Analysis of Handheld Doppler Signals to Detect Masked Peripheral Ischemia in Diabetic Patients with Normal Ankle-Brachial Index.

OBJECTIVE: The Ankle-Brachial Index (ABI) remains the primary screening tool for Peripheral Arterial Disease (PAD). However, its diagnostic performanc...

Automation in the IVF laboratory in 2026: four technology domains, an asymmetric evidence base, and the case for parallel development with clinician-side automation.

BACKGROUND: Operator-dependent laboratory tasks-embryo selection, vitrification and warming, and intracytoplasmic sperm injection (ICSI)-have been the...

Using machine learning algorithms based on laboratory indicators to establish a diagnostic model for lung cancer.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Current diagnostic strategies rely primarily on imagi...

Bibliometric analysis of research hotspots in coronary artery CT fractional flow reserve for diagnosing myocardial ischemia in coronary artery disease.

OBJECTIVE: This study aimed to conduct a comprehensive bibliometric analysis to map the global research landscape, identify evolving hotspots, and for...

Combining Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation to Explore the Mechanism of Danggui-Shaoyao-San in treating Rheumatoid arthritis.

BACKGROUND: Danggui-Shaoyao-San (DSS) demonstrates clinical efficacy in rheumatoid arthritis (RA), but its bioactive constituents and molecular mechan...

Bias-induced NO adsorption and configurational transitions on Cu(110): a machine learning enhanced first-principles grand canonical study.

Precise control over the configurational changes of molecules adsorbed on metal surfaces is critical for advancing molecular-scale technologies, inclu...