Pathology

Implementation of artificial intelligence models in magnetic resonance imaging with focus on diagnosis of rheumatoid arthritis and axial spondyloarthritis: narrative review.

Early diagnosis in rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) is essential to initiate timely interventions, such as medication and lifestyle changes, preventing irreversible joint damage, reducing symptoms, and improving long-term outcomes for patients. Since magnetic resonance imaging (MRI) of the wrist and hand, in case of RA and MRI of the sacroiliac joints (SIJ) in case of ...

Artificial intelligence scoring of liver biopsies in a phase II trial of semaglutide in nonalcoholic steatohepatitis.

BACKGROUND AND AIMS: Artificial intelligence-powered digital pathology offers the potential to quantify histological findings in a reproducible way. This analysis compares the evaluation of histological features of NASH between pathologists and a machine-learning (ML) pathology model.

Specimen Shape and Elution Time Affect the Mineralization and Differentiation Potential of Dental Pulp Stem Cells to Biodentine.

The liquid extract method is commonly used to evaluate the cytotoxicity and bioactivity of materials. Although ISO has recommended guidelines for test...

Diagnostic accuracy of endocytoscopy via artificial intelligence in colorectal lesions: A systematic review and meta‑analysis.

BACKGROUND: Endocytoscopy (EC) is a nuclei and micro-vessels visualization in real-time and can facilitate "optical biopsy" and "virtual histology" of...

Applications of Artificial Intelligence in Lung Pathology.

Artificial intelligence/machine learning tools are being created for use in pathology. Some examples related to lung pathology include acid-fast stain...

A machine learning approach for quantifying age-related histological changes in the mouse kidney.

The ability to quantify aging-related changes in histological samples is important, as it allows for evaluation of interventions intended to effect he...

Machine learning and machine teaching in histopathology.

An artificial intelligence (AI) platform was trained by a consultant histopathologist to classify whole slide images (WSIs) of large bowel biopsies. S...

Deep Learning Augmented Osteoarthritis Grading Standardization.

Manual grading of cartilage histology images for investigating the extent and severity of osteoarthritis (OA) involves critical examination of the cel...

Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for Unprocessed Prostate Biopsies.

PURPOSE: Stimulated Raman histology is an innovative technology that generates real-time, high-resolution microscopic images of unprocessed tissue, si...

Extraction Process Optimization of Curcumin from Roxb. with Supercritical Carbon Dioxide Using Ethanol as a Cosolvent.

Roxb., known as temulawak, Javanese ginger, or Javanese turmeric, is a plant species belonging to the ginger family. This plant originated in Indones...

Insight into Automatic Image Diagnosis of Ear Conditions Based on Optimized Deep Learning Approach.

Examining otoscopic images for ear diseases is necessary when the clinical diagnosis of ear diseases extracted from the knowledge of otolaryngologists...

Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.

OBJECTIVE: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We...

A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions.

Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a v...

Deployment and assessment of a deep learning model for real-time detection of anal precancer with high frame rate high-resolution microendoscopy.

Anal cancer incidence is significantly higher in people living with HIV as HIV increases the oncogenic potential of human papillomavirus. The incidenc...

From the diagnosis of infectious keratitis to discriminating fungal subtypes; a deep learning-based study.

Infectious keratitis (IK) is a major cause of corneal opacity. IK can be caused by a variety of microorganisms. Typically, fungal ulcers carry the wor...

The robotic-assisted laparoscopic approach to biliary tract resection and reconstruction for benign indications: A single-center experience.

BACKGROUND: Benign biliary disease (BBD) is a prevalent condition involving patients who require extrahepatic bile duct resections and reconstructions...

Deep Learning-Assisted Intelligent Artificial Vision Platform Based on Dual-Luminescence Eu(III)-Functionalized HOF for the Diagnosis of Breast and Ovarian Cancer.

Developing an advanced analytical method to detect spermine (Spm) and -acetylneuraminic acid (NANA), the biomarkers of breast and ovarian cancers, res...

Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo.

Enhancers control gene expression and have crucial roles in development and homeostasis. However, the targeted de novo design of enhancers with tissue...

Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images.

Recent advancements in tissue imaging techniques have facilitated the visualization and identification of various cell types within physiological and ...

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology.

INTRODUCTION: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-...