Dermatology

CT Image Analysis and Clinical Diagnosis of New Coronary Pneumonia Based on Improved Convolutional Neural Network.

In this paper, based on the improved convolutional neural network, in-depth analysis of the CT image...

Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast c...

An Evolutionary Approach for the Enhancement of Dermatological Images and Their Classification Using Deep Learning Models.

Dermatological problems are the most widely spread skin diseases amongst human beings. They can be i...

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annua...

An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images.

Diabetic retinopathy (DR) is one of the leading causes of vision loss across the world. Yet despite ...

Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

BACKGROUND: The number of naevi on a person is the strongest risk factor for melanoma; however, naev...

Lesion probability mapping in MS patients using a regression network on MR fingerprinting.

BACKGROUND: To develop a regression neural network for the reconstruction of lesion probability maps...

Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.

BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in ...

COVID-19 lesion detection and segmentation-A deep learning method.

PURPOSE: In this paper, we utilized deep learning methods to screen the positive COVID-19 cases in c...

Deep learning for categorization of endodontic lesion based on radiographic periapical index scoring system.

OBJECTIVE: The study aimed to apply convolutional neural network (CNN) to score periapical lesion on...

Use of Convolutional Neural Networks for the Detection of u-Serrated Patterns in Direct Immunofluorescence Images to Facilitate the Diagnosis of Epidermolysis Bullosa Acquisita.

The u-serrated immunodeposition pattern in direct immunofluorescence (DIF) microscopy is a recogniza...

Orthogonal quantification of soluble inducible T-cell costimulator (ICOS) in healthy and diseased human serum.

Inducible T-cell costimulator (ICOS), a homodimeric protein expressed on the surface of activated T-...

A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application.

In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before derm...

Eye-Movement-Controlled Wheelchair Based on Flexible Hydrogel Biosensor and WT-SVM.

To assist patients with restricted mobility to control wheelchair freely, this paper presents an eye...

Diving beetle-like miniaturized plungers with reversible, rapid biofluid capturing for machine learning-based care of skin disease.

Recent advances in bioinspired nano/microstructures have received attention as promising approaches ...

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction.

OBJECTIVES: To compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstru...

Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method.

Chest computed tomography (CT) image data is necessary for early diagnosis, treatment, and prognosis...

D-UNet: A Dimension-Fusion U Shape Network for Chronic Stroke Lesion Segmentation.

Assessing the location and extent of lesions caused by chronic stroke is critical for medical diagno...

Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma.

Deep learning has emerged as the technique of choice for identifying hidden patterns in cell imaging...

Unintentional consequences of artificial intelligence in dermatology for patients with skin of colour.

Accuracy of a convolutional neural network for dermatological diagnosis of tumours and skin lesions in a clinical setting.