Pathology

Dual resolution deep learning network with self-attention mechanism for classification and localisation of colorectal cancer in histopathological images.

AIMS: Microscopic examination is a basic diagnostic technology for colorectal cancer (CRC), but it is very laborious. We developed a dual resolution deep learning network with self-attention mechanism (DRSANet) which combines context and details for CRC binary classification and localisation in whole slide images (WSIs), and as a computer-aided diagnosis (CAD) to improve the sensitivity and specif...

Artificial intelligence in glomerular diseases.

In this narrative review, we focus on the application of artificial intelligence in the clinical history of patients with glomerular disease, digital pathology in kidney biopsy, renal ultrasonography imaging, and prediction of chronic kidney disease (CKD). With the development of natural language processing, the clinical history of a patient can be used to identify a computable phenotype. In kidne...

FILM: Filtering and Machine Learning for Malware Detection in Edge Computing.

Machine learning with static-analysis features extracted from malware files has been adopted to detect malware variants, which is desirable for resour...

TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification.

Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challenging task due to a variety of issues, such as col...

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.

OBJECTIVES: To build an artificial intelligence (AI) system to classify benign and malignant non-mass enhancement (NME) lesions using maximum intensit...

Application of a Deep-Learning Technique to Non-Linear Images From Human Tissue Biopsies for Shedding New Light on Breast Cancer Diagnosis.

The development of label-free non-destructive techniques to be used as diagnostic tools in cancer research is of great importance for improving the qu...

Breast cancer detection using artificial intelligence techniques: A systematic literature review.

Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has been developed for it. Breast cancer is one of the most common c...

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy.

INTRODUCTION AND OBJECTIVES: This study aims to investigate the relationship between perineural invasion (PNI) in targeted (TBx) and/or systematic (SB...

Intelligent Defect Diagnosis of Rolling Element Bearings under Variable Operating Conditions Using Convolutional Neural Network and Order Maps.

Vibration analysis is an established method for fault detection and diagnosis of rolling element bearings. However, it is an expert oriented exercise....

Robot-Assisted Prostate-Specific Membrane Antigen-Radioguided Surgery in Primary Diagnosed Prostate Cancer.

The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific membrane antigen (PSMA) robot-assisted-radioguide...

Artificial intelligence for histological subtype classification of breast cancer: combining multi-scale feature maps and the recurrent attention model.

AIMS: The aim of this study was to apply a two-stage deep model combining multi-scale feature maps and the recurrent attention model (RAM) to assist w...

Artificial Intelligence in Pediatric Pathology: The Extinction of a Medical Profession or the Key to a Bright Future?

Artificial Intelligence (AI) has become of increasing interest over the past decade. While digital image analysis (DIA) is already being used in radio...

Detection of Breast Cancer Using Histopathological Image Classification Dataset with Deep Learning Techniques.

Cancer is one of the top causes of mortality, and it arises when cells in the body grow abnormally, like in the case of breast cancer. For people all ...

Multitask Deep Learning Reconstruction and Localization of Lesions in Limited Angle Diffuse Optical Tomography.

Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to assess its optical properties and identify abnormalities....

Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.

Optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering a new mechanism of endoscopic tissue a...

Objective quantification of nerves in immunohistochemistry specimens of thyroid cancer utilising deep learning.

Accurate quantification of nerves in cancer specimens is important to understand cancer behaviour. Typically, nerves are manually detected and counted...

Predicting age at onset of type 1 diabetes in children using regression, artificial neural network and Random Forest: A case study in Saudi Arabia.

The rising incidence of type 1 diabetes (T1D) among children is an increasing concern globally. A reliable estimate of the age at onset of T1D in chil...

Tomographic Ultrasound Imaging in the Diagnosis of Breast Tumors under the Guidance of Deep Learning Algorithms.

This study was aimed to discuss the feasibility of distinguishing benign and malignant breast tumors under the tomographic ultrasound imaging (TUI) of...

Anti-Fatigue and Exercise Performance Improvement Effect of Extract in Mice.

(GT) is a native perennial plant growing across the coastline areas in Taiwan. The current study aimed to examine the efficacy of GT extract in ameli...

A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning.

Vaginitis is a gynecological disease affecting the health of millions of women all over the world. The traditional diagnosis of vaginitis is based on ...