Dermatology

Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning.

Cervical cancer is one of the most frequent cancers in women worldwide, yet the early detection and ...

A survey on incorporating domain knowledge into deep learning for medical image analysis.

Although deep learning models like CNNs have achieved great success in medical image analysis, the s...

Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects.

Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes...

Validation of artificial intelligence application in clinical dermatology.

Artificial intelligence in dermatopathology: Diagnosis, education, and research.

Artificial intelligence (AI) utilizes computer algorithms to carry out tasks with human-like intelli...

Batch Similarity Based Triplet Loss Assembled into Light-Weighted Convolutional Neural Networks for Medical Image Classification.

In many medical image classification tasks, there is insufficient image data for deep convolutional ...

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI.

One of the most common types of cancer in men is prostate cancer (PCa). Biopsies guided by bi-parame...

Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.

BACKGROUND: Studies systematically unravelling possible causes for false diagnoses of deep learning ...

Automated detection of mouse scratching behaviour using convolutional recurrent neural network.

Scratching is one of the most important behaviours in experimental animals because it can reflect it...

The future of digital dermatology.

Deep learning model for classifying endometrial lesions.

BACKGROUND: Hysteroscopy is a commonly used technique for diagnosing endometrial lesions. It is esse...

Melanoma diagnosis using deep learning techniques on dermatoscopic images.

BACKGROUND: Melanoma has become more widespread over the past 30 years and early detection is a majo...

FFU-Net: Feature Fusion U-Net for Lesion Segmentation of Diabetic Retinopathy.

Diabetic retinopathy is one of the main causes of blindness in human eyes, and lesion segmentation i...

Machine learning-based multimodal prediction of language outcomes in chronic aphasia.

Recent studies have combined multiple neuroimaging modalities to gain further understanding of the n...

Lesion-Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale.

The acquisition of large-scale medical image data, necessary for training machine learning algorithm...

Systematic Comparison of Heatmapping Techniques in Deep Learning in the Context of Diabetic Retinopathy Lesion Detection.

PURPOSE: Heatmapping techniques can support explainability of deep learning (DL) predictions in medi...

CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.

Systematic perturbation of cells followed by comprehensive measurements of molecular and phenotypic ...

Pathological myopia classification with simultaneous lesion segmentation using deep learning.

BACKGROUND AND OBJECTIVES: Pathological myopia (PM) is the seventh leading cause of blindness, with ...

Can an Artificial Intelligence Decision Aid Decrease False-Positive Breast Biopsies?

This study aimed to evaluate the effect of an artificial intelligence (AI) support system on breast ...

AF-SENet: Classification of Cancer in Cervical Tissue Pathological Images Based on Fusing Deep Convolution Features.

Cervical cancer is the fourth most common cancer in the world. Whole-slide images (WSIs) are an impo...

Knowledge transfer between brain lesion segmentation tasks with increased model capacity.

Convolutional neural networks (CNNs) have become an increasingly popular tool for brain lesion segme...