Pathology

Integration of histopathological characteristics by machine learning improves the prediction of neoadjuvant immunochemotherapy response in triple-negative breast cancer.

Neoadjuvant immunochemotherapy (NAIC) is a standard treatment for triple-negative breast cancer (TNBC), but there is no reliable biomarker to identify potential responders and optimize patient care. In this study, we developed a model named Immunotherapy Prediction based on Pathological Images (IPPI) by machine learning. The IPPI model performed well in the discovery cohort and two validation coho...

Single-cell and machine learning-based analysis of the molecular mechanism of Banxia Xiexin Decoction in the treatment of gastric cancer.

UNLABELLED: Gastric cancer (GC) is one of the most common malignant tumors worldwide. Banxia Xiexin Decoction (BXXXD) has a significant therapeutic effect on digestive system diseases, but its mechanism of action on GC is not yet clear. Using single-cell and bioinformatics to discover prognostic markers and Tumor Microenvironment (TME) components for GC, and further explore the molecular mechanism...

AI-Driven Coverage-Dependent Kinetics for NH3 Synthesis on Fe(110).

Adsorbate-adsorbate interaction serves as a critical bridge between macroscopic mass transfer and microscopic adsorption-reaction kinetics in heteroge...

A Multimodal Approach for Deep-Learning Classification of Vocal Fold Pathologies in Stroboscopy.

OBJECTIVE: To develop and validate a multimodal deep-learning classifier trained on stroboscopic image, voice, and clinicodemographic data, differenti...

FTIR spectroscopy combined with machine learning reveals molecular signatures distinguishing three phenotypes of endometriosis.

Endometriosis is a chronic inflammatory disorder in which endometrial tissue grows outside the uterus, leading to pelvic pain and infertility. It rema...

Identifying transcriptional signatures of leukocytes in tissue and blood for multicancer diagnosis by using machine learning methods.

Investigating the transcriptional signatures of immune cells in various cancer types is crucial for understanding their roles in the tumor microenviro...

The role of focal therapy for localized prostate cancer: From diagnosis to ablation.

INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...

Noninvasive real-time dynamic monitoring of white blood cells based on microscopic imaging and deep learning.

BACKGROUND AND OBJECTIVE: White blood cells (WBCs) are key biomarkers of immune status, but current monitoring still relies on intermittent blood samp...

Multicellular, Biochemical, and Perfusion Effects on Vessel Network Morphogenesis in a Microfluidic Vasculature-on-a-Chip.

Microvascular networks (MVNs) formed via endothelial cell self-assembly in 3D hydrogels have emerged as a widely used platform for modeling vasculariz...

Impact of image processing techniques on deep learning-based classification accuracy of cervical vertebral maturation.

OBJECTIVES: This research aimed to investigate how different image processing techniques influence the performance of a deep learning model in classif...

Deep Learning Integration in Optical Microscopy: Advancements and Applications.

Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution l...

Classification of Salivary Gland Tumors on Ultrasound Using Artificial Intelligence: A Systematic Review and Meta-Analysis.

OBJECTIVE: Accurate classification of salivary gland tumors is critical to guiding appropriate management. This study evaluates the diagnostic perform...

Minimally Invasive, Label-Free, Point-of-Care Histopathological Diagnostic Platform of Malignant Tumors of the Female Reproductive System Based on Raman Spectroscopy and Machine Learning.

Fast intraoperative histopathology is critical for optimal surgery in ovarian, endometrial and cervical cancers, yet frozen-section pathology is slow ...

Leveraging Interpretable AI for Deciphering Signature Histopathologic Patterns.

BACKGROUND: Leukocytoclastic vasculitis (LCV) and microvascular occlusion (MVO) are distinct histopathologic patterns underlying dermatologic diagnose...

Design and rationale of the WARRIOR ancillary study for coronary CT angiographic analysis.

BACKGROUND: Over 50% of women evaluated for suspected ischemia have no obstructive coronary artery disease (INOCA). Statins, angiotensin converting en...

A droplet digital LAMP-based lab-on-a-disc system for multiplex allele-specific detection of tumor-derived DNA mutations.

The absence of accurate, rapid, fully automated, and cost-effective detection methods has hindered the clinical translation of tumor-derived DNA mutat...

SegRenal: AI-Driven segmentation of frozen sections in transplant kidney biopsies - A comparative analysis of deep learning models.

BACKGROUND AND OBJECTIVE: Frozen section evaluation of donor kidney biopsies is vital for determining transplant suitability, yet remains challenging ...

Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.

Metabolic alterations and immune dysfunction within the gastric tumor microenvironment critically drive gastric cancer (GC) progression and therapeuti...

Artificial intelligence as a tool for bionomic transects: the case of Isidella elongata (Esper, 1788) forests in the Western Mediterranean.

Deep-sea ecosystems are among the least explored on Earth, and traditional sampling methods often underestimate fragile megabenthic species such as go...

A Multimodal Large Language Model Framework for Clinical Subtyping and Malignant Transformation Risk Prediction in Oral Lichen Planus: A Paired Comparison With Expert Clinicians.

BACKGROUND: Oral lichen planus (OLP), oral lichenoid lesions (OLL), and squamous cell carcinoma on a lichenoid background (SCC-over-LP/LLP) overlap cl...