Latest AI and machine learning research in pathology for healthcare professionals.
Osteoarthritis (OA) is a chronic joint disorder characterized by pain, reduced mobility, and structural degeneration. Despite its complex etiology and multi-tissue involvement, the molecular mechanisms underlying OA remain poorly understood. This study aimed to identify tissue-specific diagnostic biomarkers using an integrative framework combining multiple machine learning (ML) algorithms and SHap...
Multimodal cell microscopic image segmentation is a core component of high-content imaging and analysis (HCIA) technology, and its segmentation accuracy directly impacts the precision of HCIA analysis results. Deep learning-based cell segmentation methods have been widely applied due to their end-to-end nature. However, when processing multimodal cell microscopy images, challenges such as missed c...
The traditional paradigm of pathology diagnosis faces challenges like data fragmentation and inefficiency in the era of big data and artificial intell...
BACKGROUND: Proton density fat fraction (PDFF) measured using magnetic resonance imaging (MRI) is considered a noninvasive reference measure of fat de...
INTRODUCTION/AIMS: Myasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been...
BACKGROUND: Nasal polyps (NP) are common upper respiratory conditions with diverse inflammatory subtypes influencing clinical features and prognosis. ...
BACKGROUND: Artificial intelligence enhances pathology screening efficiency, yet clinical adoption remains limited because most systems operate as opa...
Automated detection of entomopathogenic nematodes (EPNs) is increasingly important in biological control research, where manual microscopic counting r...
ETHNOPHARMACOLOGICAL RELEVANCE: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by symptoms such as persistent diarrhea....
Medical imaging plays a central role in modern clinical decision-making by transforming raw image data into actionable diagnostic insights. In the con...
Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is ...
Right ventricular (RV) enlargement or dysfunction evaluation is the cornerstone for diagnosis, prognostications, and treatment planning in a variety o...
Nitenpyram (NIT) is an insecticide used primarily for flea control in pets, especially cats and dogs. Some studies suggest that NIT is associated with...
This study presents an incremental learning framework to enhance the generalization and robustness of transformer-based deep learning models for segme...
Alzheimer's Disease (AD) is a degenerative disorder of the brain that causes a gradual loss of cognitive function. The cholinergic hypothesis suggests...
Glioblastoma multiforme (GBM), the most malignant subtype of glioma, poses significant diagnostic challenges due to limitations in current methods, su...
BACKGROUND: Women with a history of breast cancer face an elevated risk of developing contralateral breast cancer (CBC). Although annual mammographic ...
BACKGROUND: Early detection of cancer and precise recurrence monitoring remain major unmet needs in oncology. Conventional screening is limited to a f...
The aim of the study was to evaluate the concordance between radiological imaging modalities and pathological findings and to test whether neoadjuvant...
MicroRNAs (miRNAs) serve as crucial biomarkers in disease diagnosis. Although silicon-based electronic machine learning models provide efficient means...