Pathology

A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.

Onychomycosis is common. Diagnosis can be confirmed by various methods; a commonly used method is the histological examination of nail clippings. A deep learning system was developed and its diagnostic accuracy compared with that of human experts. A dataset with annotations for fungal elements was used to train an artificial intelligence (AI) model. In a second dataset (n=199) the diagnostic accur...

Differentiating Benign from Malignant Renal Tumors Using T2- and Diffusion-Weighted Images: A Comparison of Deep Learning and Radiomics Models Versus Assessment from Radiologists.

BACKGROUND: Differentiating benign from malignant renal tumors is important for selection of the most effective treatment.

The effect of consuming different proportions of hummer fish on biochemical and histopathological changes of hyperglycemic rats.

Hammour fish (grouper fish) are known to be of great nutritional value for human consumption, as their protein has a high biological value and contain...

AAWS-Net: Anatomy-aware weakly-supervised learning network for breast mass segmentation.

Accurate segmentation of breast masses is an essential step in computer aided diagnosis of breast cancer. The scarcity of annotated training data grea...

NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.

Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challenging molecular underpinnings and clinical managemen...

Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN).

The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate...

A deep learning-machine learning fusion approach for the classification of benign, malignant, and intermediate bone tumors.

OBJECTIVES: To build and validate deep learning and machine learning fusion models to classify benign, malignant, and intermediate bone tumors based o...

Transcorneal delivery of topically applied silver nanoparticles does not delay epithelial wound healing.

Silver nanoparticles (AgNPs) are a common antimicrobial additive for a variety of applications, including wound care. However, AgNPs often undergo dis...

Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.

Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image...

Development of a gold-nanorod-based lateral flow immunoassay for a fast and dual-modal detection of C-reactive protein in clinical plasma samples.

Fast and simple detection of C-reactive protein (CRP) is highly significant for the diagnosis and prognosis of inflammatory or infectious diseases. La...

Discriminative deep learning based benignity/malignancy diagnosis of dermatologic ultrasound skin lesions with pretrained artificial intelligence architecture.

BACKGROUND: Deep-learning algorithms (DLAs) have been used in artificial intelligence aided ultrasonography diagnosis of thyroid and breast lesions. H...

Semi-HIC: A novel semi-supervised deep learning method for histopathological image classification.

Histopathological images provide a gold standard for cancer recognition and diagnosis. Existing approaches for histopathological image classification ...

Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy.

Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting sem...

DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning.

A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular...

Method for Diagnosis of Acute Lymphoblastic Leukemia Based on ViT-CNN Ensemble Model.

Acute lymphocytic leukemia (ALL) is a deadly cancer that not only affects adults but also accounts for about 25% of childhood cancers. Timely and accu...

Assessment of Axillary Lymph Nodes for Metastasis on Ultrasound Using Artificial Intelligence.

The purpose of this study was to evaluate an artificial intelligence (AI) system for the classification of axillary lymph nodes on ultrasound compared...

Diagnosis of Wilson Disease and Its Phenotypes by Using Artificial Intelligence.

WD is caused by variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challe...

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to ide...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment, such as extracellular matrix remodeling, recipro...

Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network.

Direct microscopic examination with potassium hydroxide is generally used as a screening method for diagnosing superficial fungal infections. Although...