Pathology

MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification.

Distinguishing malignant from benign lesions has significant clinical impacts on both early detectio...

Exploring Dual-Energy CT Spectral Information for Machine Learning-Driven Lesion Diagnosis in Pre-Log Domain.

In this study, we proposed a computer-aided diagnosis (CADx) framework under dual-energy spectral CT...

Applied machine learning in hematopathology.

An increasing number of machine learning applications are being developed and applied to digital pat...

Ensemble-based multi-tissue classification approach of colorectal cancer histology images using a novel hybrid deep learning framework.

Colorectal cancer (CRC) is the second leading cause of cancer death in the world, so digital patholo...

Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer.

Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the inv...

ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification.

BACKGROUND AND OBJECTIVE: Histopathology is the gold standard for diagnosis of many cancers. Recent ...

Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics.

PURPOSE: Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnosti...

Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.

How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous ...

Use of systems with deep learning and machine learning for the detection and classification of malignant vs. benign spinal fractures with MRI: can deep/machine learning help us further for detection and characterization?

Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer.

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we pr...

Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.

Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily eva...

Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers.

This study aimed to develop an algorithm to automatically segment the oral potentially malignant dis...

Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images.

In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of charact...

A comparison of point-tracking algorithms in ultrasound videos from the upper limb.

Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion...

A state-of-the-art survey of artificial neural networks for Whole-slide Image analysis: From popular Convolutional Neural Networks to potential visual transformers.

In recent years, with the advancement of computer-aided diagnosis (CAD) technology and whole slide i...

Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.

OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogen...

Cancer prediction from few amounts of histology samples through self-attention based multi-routines cross-domains network.

OBJECTIVE: Rapid and efficient analysis of cancer has become a focus of research. Artificial intelli...

Classification of breast tumors by using a novel approach based on deep learning methods and feature selection.

PURPOSE: Cancer is one of the most insidious diseases that the most important factor in overcoming t...

Radiomics and artificial intelligence for precision medicine in lung cancer treatment.

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic ...

A deep learning-based automated image analysis for histological evaluation of broiler pectoral muscle.

Global market demand for chicken breast muscle with high yield and quality, together with the high i...

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of auto...