Dermatology

Latest AI and machine learning research in dermatology for healthcare professionals.

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Subcategories: Atopy Psoriasis
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Multimodal Sensors with Decoupled Sensing Mechanisms.

Highly sensitive and multimodal sensors have recently emerged for a wide range of applications, incl...

Ability to Predict Melanoma Within 5 Years Using Registry Data and a Convolutional Neural Network: A Proof of Concept Study.

Research relating to machine learning algorithms, including convolutional neural networks, has incre...

Development and clinical applicability of MRI-based 3D prostate models in the planning of nerve-sparing robot-assisted radical prostatectomy.

The interpretation of conventional MRI may be limited by the two-dimensional presentation of the ima...

DTP-Net: A convolutional neural network model to predict threshold for localizing the lesions on dermatological macro-images.

Highly focused images of skin captured with ordinary cameras, called macro-images, are extensively u...

Rainfall prediction using multiple inclusive models and large climate indices.

Rainfall prediction is vital for the management of available water resources. Accordingly, this stud...

Artificial intelligence for the automated single-shot assessment of psoriasis severity.

BACKGROUND: PASI score is globally used to assess disease activity of psoriasis. However, it is rela...

Development of Lymphopenia during Therapy with Immune Checkpoint Inhibitors Is Associated with Poor Outcome in Metastatic Cutaneous Melanoma.

Predictive markers for immune checkpoint inhibitor (ICI) therapy are needed. Thus, baseline blood co...

A Hybrid Deep Transfer Learning of CNN-Based LR-PCA for Breast Lesion Diagnosis via Medical Breast Mammograms.

One of the most promising research areas in the healthcare industry and the scientific community is ...

MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping.

To the best of our knowledge, artificial intelligence stain generation is an urgent requirement for ...

An Online Prognostic Application for Melanoma Based on Machine Learning and Statistics.

BACKGROUND: Melanoma is a common cancer that causes a severe socioeconomic burden. Patients usually ...

Size-adaptive mediastinal multilesion detection in chest CT images via deep learning and a benchmark dataset.

PURPOSE: Many deep learning methods have been developed for pulmonary lesion detection in chest comp...

Diagnostic performance of artificial intelligence approved for adults for the interpretation of pediatric chest radiographs.

Artificial intelligence (AI) applied to pediatric chest radiographs are yet scarce. This study evalu...

Systematic perturbation of an artificial neural network: A step towards quantifying causal contributions in the brain.

Lesion inference analysis is a fundamental approach for characterizing the causal contributions of n...

Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest.

Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM)...

Deep learning for image-based liver analysis - A comprehensive review focusing on malignant lesions.

Deep learning-based methods, in particular, convolutional neural networks and fully convolutional ne...

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based o...

Data-Driven Deep Supervision for Medical Image Segmentation.

Medical image segmentation plays a vital role in disease diagnosis and analysis. However, data-depen...

AcneGrader: An ensemble pruning of the deep learning base models to grade acne.

BACKGROUND: Acne is one of the most common skin lesions in adolescents. Some severe or inflammatory ...

Dermoscopic Image Classification of Pigmented Nevus under Deep Learning and the Correlation with Pathological Features.

The objective of this study was to explore the image classification and case characteristics of pigm...

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