Latest AI and machine learning research in pathology for healthcare professionals.
Artificial intelligence (AI) has emerged as a transformative tool in liver imaging, offering enhanced diagnostic accuracy, efficiency, and reproducibility. The integration of machine learning and deep learning algorithms into radiological workflows has shown significant promise across a wide range of liver diseases. Key applications include automated liver segmentation on computed tomography (CT) ...
INTRODUCTION: Optimizing the diagnostic approach to thyroid nodules remains a crucial challenge. Ultrasound-based risk stratification systems such as EU-TIRADS have shown reasonable sensitivity and specificity. Therefore, we conducted a systematic review and meta-analysis to assess the diagnostic performance of Artificial Intelligence (AI) models in differentiating benign from malignant thyroid no...
Prostate cancer is a prevalent and serious health concern, ranking among the most frequently diagnosed cancers and a leading cause of cancer-related d...
A microscope is essential in scientific and medical research, enabling the magnification of specimens too small for the naked eye. The conventional me...
OBJECTIVES: The aim of this study was to evaluate the impact of introducing an autonomous courier in a clinical laboratory, focusing on specimen turna...
PURPOSE OF REVIEW: To review contemporary applications, performance, and implementation challenges of artificial intelligence (AI) in the radiological...
Signal transduction is a complex system governing cellular behavior across physiological and pathological contexts. Advances in systems biology have p...
Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current ap...
BACKGROUND/AIM: Metabolic dysfunction-associated steatotic liver disease (MASLD) is often silent and progressive, affecting nearly one-fourth of the g...
Artificial intelligence (AI) is rapidly reshaping gynecologic oncology across the continuum of care. This clinician-focused review synthesizes current...
BACKGROUND & AIMS: The incidence of early-onset colorectal cancer (EOCRC; diagnosed before age 50 years) continues to increase, now standing as the le...
INTRODUCTION: Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are ur...
OBJECTIVE: The goal of this study was to curate a prostate MRI dataset from a screening population and to train and evaluate a deep-learning segmentat...
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) provides a standardised framework for thyroid fine needle aspiration cyto...
INTRODUCTION: The global incidence of skin cancer is rising, emphasizing the need for early detection tools. Artificial intelligence (AI) models, incl...
Neuronal circuits are the key target of both evolutionary and individual adaptation that enable organisms to successfully navigate, predict and shape ...
OBJECTIVES: This study describes and evaluates the functionality of the InVivo7 3D imaging software as a semi-automated tool for identifying craniofac...
Mild traumatic brain injury typically produces no abnormalities on neuroimaging yet elicits symptoms that, in an increasing fraction of survivors, lin...
With the development of digital imaging in medical microscopy, artificial intelligent-based analysis of pathological whole slide images (WSIs) provide...
With the advent of novel cancer treatment options such as immunotherapy, studying the tumour immune micro-environment (TIME) is crucial to inform on p...