AIMC Topic: Skin Neoplasms
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Cross-convolutional transformer for automated multi-organs segmentation in a variety of medical images.
Physics in medicine and biology
Jan 23, 2023
It is a huge challenge for multi-organs segmentation in various medical images based on a consistent algorithm with the development of deep learning methods. We therefore develop a deep learning method based on cross-convolutional transformer for the...
Deep learning as a new tool in the diagnosis of mycosis fungoides.
Archives of dermatological research
Dec 26, 2022
Mycosis Fungoides (MF) makes up the most of the cutaneous lymphomas. As a malignant disease, the greatest diagnostical challenge is to timely differentiate MF from inflammatory diseases. Contemporary computational methods successfully identify cell n...
A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients.
Scientific reports
Nov 27, 2022
The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival...
Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.
Medical image analysis
Nov 24, 2022
Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of computational pathology tasks, this performance often markedly deteriorates on whole slide images (WSI) generated at external test sites. This phenomenon ...
Viscoelasticity assessment of tumoral skin with the use of a novel contact-free palpation methodology based upon surface waves.
Scientific reports
Nov 4, 2022
The ensuing pilot investigation sheds new light on characterizing tumoral and non-tumoral human skin mechanical properties that will not only assist the dermatologist's diagnosis but also could constitute the creation of an Artificial Intelligence da...
SkiNet: A deep learning framework for skin lesion diagnosis with uncertainty estimation and explainability.
PloS one
Oct 31, 2022
Skin cancer is considered to be the most common human malignancy. Around 5 million new cases of skin cancer are recorded in the United States annually. Early identification and evaluation of skin lesions are of great clinical significance, but the di...
Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network.
Acta dermato-venereologica
Oct 11, 2022
Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with...
Skin Lesion Classification on Imbalanced Data Using Deep Learning with Soft Attention.
Sensors (Basel, Switzerland)
Oct 4, 2022
Today, the rapid development of industrial zones leads to an increased incidence of skin diseases because of polluted air. According to a report by the American Cancer Society, it is estimated that in 2022 there will be about 100,000 people suffering...
Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset.
Scientific data
Sep 27, 2022
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approaches have proven their potential for supporting pathologists in this re...
Classification of Skin Cancer Lesions Using Explainable Deep Learning.
Sensors (Basel, Switzerland)
Sep 13, 2022
Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Re...
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