Latest AI and machine learning research in pathology for healthcare professionals.
Tissue architecture is a product of a multilayered molecular landscape, where even subtle disruptions in the spatial context can initiate or reflect disease processes. Recent advances in high-throughput spatial omics technologies have enabled the investigation of this complexity in stunning detail, providing groundbreaking insights into how spatial molecular organization shapes health and disease....
Accurate prognostic stratification is essential for optimizing postoperative therapeutic strategies in oncology. While deep learning approaches have shown promise for survival prediction through unimodal analyses of histopathological images, transcriptomic profiles, and microbial signatures, their clinical utility remains limited due to fragmented biological insights. In this study, we introduce H...
OBJECTIVES: To develop and validate an ultrasonography-based machine learning (ML) model for predicting malignant endometrial and cavitary lesions. ME...
Deep learning (DL) has emerged as a powerful tool for modeling unstructured data, thereby improving prediction accuracy and expanding the application ...
OBJECTIVE: This study investigates the diagnostic potential of nicotinamide N-methyltransferase (NNMT) and NM23A as biomarkers for renal cell carcinom...
Abdominal aortic aneurysm (AAA) is a progressive and life-threatening vascular disorder characterized by abnormal dilation of the abdominal aorta and ...
Gastric cancer is among the most common diseases worldwide and can lead to fatal outcomes. Early diagnosis significantly increases the success of trea...
OBJECTIVES: This study aimed to develop and validate a two-stage deep learning method for diagnosing oral potentially malignant disorders (OPMDs). We ...
PURPOSE: Diagnostics for urothelial carcinoma have low sensitivity, thereby negatively impacting diagnostic outcomes. Herein, we present BiovueUro, a ...
Bloodstain pattern analysis (BPA) is increasingly shifting towards more objective methodologies for pattern classification. This transition can involv...
Colorectal cancer (CRC) is the third most common cause of cancer-related morbidity and mortality in the world. Radiomics and radiogenomics are utilize...
OBJECTIVES: Constructing a multi-task global decision support system based on preoperative enhanced CT features to predict the mismatch repair (MMR) s...
Ocular blood flow imaging techniques have become indispensable in current clinical practice because retinal vascular disturbances have been implicated...
Evidence for the ongoing biodiversity crisis rests on assessment of a small fraction of described species, with major knowledge gaps for most organism...
Traditionally, CT has been the go-to method for visualizing bone structures, while MRI has been preferred for assessing soft tissues, because structur...
There is considerable evidence implicating maternal immune activation (MIA) and cytokine dysregulation in the pathophysiology of Autism. However, cyto...
BACKGROUND & AIMS: Immune checkpoint inhibitor-based combination therapy has demonstrated high objective response rates in patients with hepatocellula...
Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, ther...
Focal cortical dysplasia (FCD) is a neurodevelopmental malformation that often manifests as medically refractory epilepsy. A key histological hallmark...
Medical images play a pivotal role in disease diagnosis. Numerous studies on cancer image analysis focus on end-to-end deep neural networks, neglectin...