Pathology

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, including single-molecule junctions and molecular switches. A bias voltage applied via scanning tunneling microscopy (STM) enables such control by inducing configurational switching through electron injection/extraction. However, gaining atomistic insight...

Comparison of Gram stain interpretation accuracy between a computer-aided diagnosis app and microbiology specialists in blood culture samples.

UNLABELLED: Gram staining is one of the basic tests to identify the organism in microbiological laboratory, especially in blood culture. However, microbiological specialists are not always available, which can lead to treatment delays. Therefore, we developed a computer-aided diagnosis (CAD) system that uses artificial intelligence to predict causative pathogens from Gram-stained blood culture ima...

Development of a precise saliva-based epigenetic clock using a six-CpG-marker panel.

Saliva, a frequently encountered biological specimen in forensic investigations, has great potential to provide critical leads if the donor's age can ...

Identification and Intelligent Prediction of Microscopic Residual Oil Distribution Based on the TransUNet Neural Network.

The morphological distribution and classification of remaining oil are of great significance to oilfield development. Traditional identification and c...

Upconversion Nanoparticle-Guided Virtual Deformable Mirror for Computational Adaptive Optics in Scattering Fluorescence Microscopy.

Fluorescence microscopy in deep tissue is strongly degraded by optical aberrations, leading to reduced signal-to-noise ratio and spatial resolution. C...

Hierarchical Semantic Concept Modeling for Generalizable Myocardial Pathology Segmentation on Multisequence CMR Images.

Myocardial pathology segmentation (MyoPS) aims to accurately quantify myocardial scar and edema, which is critical for precise assessment of myocardia...

High-throughput machine learning-aided antibody discovery for cell surface antigens.

Machine learning (ML) has the potential to revolutionize antibody design and selection, but its success depends on access to well-curated datasets of ...

Engineering the esophagus: advances, challenges, and translational pathways in esophageal tissue reconstruction.

Esophageal reconstruction is one of the most challenging procedures in gastrointestinal surgery. While conventional therapeutic approaches, such as ga...

AI-Assisted HER2 Scoring in Breast Cancer: Diagnostic Agreement and Understanding Discordance.

PURPOSE: With trastuzumab deruxtecan demonstrating clinical benefit in HER2-low and ultralow breast cancer, precise discrimination at the lowest end o...

Human organ-on-a-chip technology as a catalyst for drug discovery.

The pharmaceutical industry currently faces a critical attrition crisis, with approximately 90% of drug candidates failing during clinical translation...

Integrated bioinformatics, machine learning, and experimental validation identify a four-gene diagnostic signature for cervical cancer associated with PI3K/AKT signaling.

Early and accurate diagnosis remains a major challenge in cervical cancer management. This study aimed to identify reliable diagnostic biomarkers for ...

Identification and validation of BLK and OSBPL10 as diagnostic and prognostic biomarkers for nasopharyngeal carcinoma through machine learning algorithms.

Despite substantial advances in radiotherapy and chemotherapy for nasopharyngeal carcinoma (NPC), a subset of patients still develops metastasis or re...

IVCM-Insight: automated interactive interpretation of in vivo confocal microscopy.

In vivo confocal microscopy (IVCM) is a critical ophthalmic examination that provides in vivo cytological and neurological information essential for d...

Multimodal integration of pathomics and clinical features improves recurrence risk prediction in pediatric medulloblastoma.

BACKGROUND: Accurate prediction of recurrence in pediatric medulloblastoma remains challenging with clinical variables alone. This study evaluated whe...

A Two-Stage, Semi-Supervised Deep Learning Framework for the Detection and Classification of Ambient Pollen using Evanescent Wave Scattering.

Airborne pollen, an aeroallergen, impacts human health, particularly as climate change shifts pollen dynamics, requiring accurate monitoring to suppor...

[Current status and progress of prognostic evaluation in marginal zone lymphoma].

Marginal zone lymphoma (MZL) is an indolent B-cell non-Hodgkin lymphoma with marked heterogeneity. Currently, histological subtype, clinical stage, bi...

The Value of a Predictive Model Based on Multimodal Ultrasound Imaging Biomarkers Combined with Clinical Features in the Diagnosis of Thyroid Nodules.

INTRODUCTION: This study aimed to develop and validate diagnostic models for distinguishing benign and malignant thyroid nodules. METHODS: Between Jan...

Performance of the Techcyte AI-based image analysis system for coproparasitological diagnosis in clinical stool specimens: a retrospective evaluation study.

UNLABELLED: Coproparasitological stool analysis based on microscopic examination is the reference diagnostic technique routinely performed in clinical...

Comparison of Deep Learning Approaches for Extreme Low-SNR Image Restoration.

BACKGROUND: Live-cell fluorescence microscopy enables the study of dynamic cellular processes. However, fluorescence microscopy can damage cells and d...

High-Throughput Olink Proteomics Elucidates the Immuno-Neurological Landscape of Gastric Cancer.

Gastric cancer (GC) ranks as the third leading cause of cancer-related mortality globally. A comprehensive and precise proteomic study of GC tissues c...