AIMC Topic: Skin Neoplasms

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Whole-slide margin control through deep learning in Mohs micrographic surgery for basal cell carcinoma.

Experimental dermatology Mar 3, 2021
BACKGROUND: Basal cell carcinoma (BCC) is the most common type of skin cancer with incidence rates rising each year. Mohs micrographic surgery (MMS) is most often chosen as treatment for BCC on the face for which each frozen section has to be histolo...
Deep Learning Neoplasm Invasiveness Margins of Excision Mohs Surgery Humans Skin Neoplasms Carcinoma, Basal Cell
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Comparison of performance of a deep learning-based mobile application with non-dermatologist physicians in the diagnosis of common skin diseases.

International journal of dermatology Mar 2, 2021
Dermoscopy Deep Learning Mobile Applications Skin Diseases Humans Physicians Skin Neoplasms
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A hierarchical three-step superpixels and deep learning framework for skin lesion classification.

Methods (San Diego, Calif.) Feb 19, 2021
Skin cancer is one of the most common and dangerous cancer that exists worldwide. Malignant melanoma is one of the most dangerous skin cancer types has a high mortality rate. An estimated 196,060 melanoma cases will be diagnosed in 2020 in the USA. M...
Humans Algorithms Deep Learning Bayes Theorem Skin Diseases Melanoma Skin Neoplasms Dermoscopy
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Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model.

AJNR. American journal of neuroradiology Feb 4, 2021
BACKGROUND AND PURPOSE: Malignant melanoma is an aggressive skin cancer in which brain metastases are common. Our aim was to establish and evaluate a deep learning model for fully automated detection and segmentation of brain metastases in patients w...
Humans Melanoma Skin Neoplasms Magnetic Resonance Imaging Brain Neoplasms Automation Deep Learning
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Artificial intelligence in dermatopathology: Diagnosis, education, and research.

Journal of cutaneous pathology Jan 26, 2021
Artificial intelligence (AI) utilizes computer algorithms to carry out tasks with human-like intelligence. Convolutional neural networks, a type of deep learning AI, can classify basal cell carcinoma, seborrheic keratosis, and conventional nevi, high...
Nevus Keratosis, Seborrheic Diagnostic Tests, Routine Observer Variation Pathology Deep Learning Diagnosis, Differential Dermatology Artificial Intelligence Machine Learning Humans Algorithms Skin Neoplasms Research Neural Networks, Computer Melanoma Carcinoma, Basal Cell
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Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.

European journal of cancer (Oxford, England : 1990) Jan 16, 2021
BACKGROUND: Studies systematically unravelling possible causes for false diagnoses of deep learning convolutional neural networks (CNNs) are scarce, yet needed before broader application.
Nevus Predictive Value of Tests Image Interpretation, Computer-Assisted Melanoma Artifacts Skin Neoplasms Cross-Sectional Studies Diagnosis, Computer-Assisted Dermoscopy Deep Learning Reproducibility of Results Humans Retrospective Studies
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Robustness of convolutional neural networks in recognition of pigmented skin lesions.

European journal of cancer (Oxford, England : 1990) Jan 7, 2021
BACKGROUND: A basic requirement for artificial intelligence (AI)-based image analysis systems, which are to be integrated into clinical practice, is a high robustness. Minor changes in how those images are acquired, for example, during routine skin c...
Humans Neural Networks, Computer Dermoscopy Reproducibility of Results Image Interpretation, Computer-Assisted Melanoma Nevus Skin Neoplasms Diagnosis, Computer-Assisted Diagnosis, Differential Predictive Value of Tests
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Universal adversarial attacks on deep neural networks for medical image classification.

BMC medical imaging Jan 7, 2021
BACKGROUND: Deep neural networks (DNNs) are widely investigated in medical image classification to achieve automated support for clinical diagnosis. It is necessary to evaluate the robustness of medical DNN tasks against adversarial attacks, as high-...
Radiography, Thoracic Photography Diagnostic Imaging Tomography, Optical Coherence Image Interpretation, Computer-Assisted Humans Skin Neoplasms Pneumonia Diabetic Retinopathy Neural Networks, Computer
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Melanoma diagnosis using deep learning techniques on dermatoscopic images.

BMC medical imaging Jan 6, 2021
BACKGROUND: Melanoma has become more widespread over the past 30 years and early detection is a major factor in reducing mortality rates associated with this type of skin cancer. Therefore, having access to an automatic, reliable system that is able ...
Humans Melanoma ROC Curve Image Interpretation, Computer-Assisted Skin Neoplasms Dermoscopy Deep Learning
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Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers.

Cancer research Dec 21, 2020
Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists...
Melanoma Algorithms Melanoma, Cutaneous Malignant Skin Neoplasms Prognosis Image Interpretation, Computer-Assisted Biomedical Research Reproducibility of Results Female Humans Medical Oncology Neoplasms Image Processing, Computer-Assisted Datasets as Topic Sensitivity and Specificity Machine Learning Lymphocytes, Tumor-Infiltrating Breast Neoplasms Predictive Value of Tests Software
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