Latest AI and machine learning research in pathology for healthcare professionals.
BACKGROUND/AIMS: Infectious keratitis (IK) is a major cause of blindness worldwide, requiring prompt diagnosis and management. This study evaluates the diagnostic and evaluative roles of in vivo confocal microscopy (IVCM) and anterior segment optical coherence tomography (AS-OCT) in acute IK through correlating the characteristic imaging features of both modalities. MATERIALS AND METHODS: In this ...
BACKGROUND: Spirometry remains the gold standard for assessing pulmonary function. Deep learning models have demonstrated potential for estimating measurements from chest X-rays (CXR). We aim to effectively address anatomical variability and integrate probabilistic reasoning to enhance estimation reliability near diagnostic thresholds. METHODS: We developed a probabilistic machine learning framewo...
BACKGROUND: Degenerative temporomandibular joint diseases (TMJ-DJD) are increasingly affecting elderly populations, with aging being a significant ris...
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract involving complex interactions among epi...
Artificial intelligence (AI) is rapidly transforming healthcare, supporting disease management and enabling outcome prediction across multiple clinica...
BACKGROUND AIMS: Computed tomography enterography (CTE) is a non-invasive cross-sectional imaging modality routinely used for diagnosis of Crohn's dis...
Breast cancer is a heterogeneous disease comprising distinct molecular subtypes that require accurate diagnosis for effective treatment. Conventional ...
Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving crit...
BACKGROUND: Prostate cancer (PCa) is characterized by pronounced intratumoral heterogeneity and multifocality, presenting ongoing challenges for early...
Single-molecule fluorescence in situ hybridization (smFISH) has emerged as a powerful tool to study gene expression dynamics with unparalleled precisi...
BACKGROUND AND OBJECTIVES: Artificial intelligence was shown to improve diagnostic accuracy for skin cancer detection. While most clinically approved ...
Many cancers are characterized by the coordinated dysregulation of multiple small noncoding RNAs (sncRNAs), yet fluorescence-based assays such as quan...
BACKGROUND: General-purpose vision-language models can analyze medical images without task-specific training, but their value for pediatric abdominal ...
Glioblastoma multiforme (GBM) represents the most aggressive primary brain tumor in adults, characterized by significant heterogeneity, rapid progress...
OBJECTIVES: To develop and validate a machine learning (ML) model integrating dual elastography, clinical features, and serum biomarkers for noninvasi...
Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy, with frequent seizures often leading to cognitive, emotional, and psychiatri...
Retrieving optical information from photons traversing scattering media is essential in fields relating to detection and imaging. Raman spectroscopy o...
Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-deri...
BackgroundSalivary gland tumors are heterogeneous, making diagnosis challenging. Artificial intelligence (AI) is a potential adjunct in diagnosis, tho...
BACKGROUND: Sjögren's syndrome (SS) is a systemic autoimmune disorder characterized by chronic inflammation, oxidative stress, and progressive salivar...