AIMC Topic: Keratosis, Seborrheic

Clear Filters Showing 1 to 8 of 8 articles

The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery Sep 6, 2024
OBJECTIVE: The incidence of non-melanoma skin cancers, encompassing basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), is on the rise globally and new methods to improve skin malignancy diagnosis are necessary. This study aims t...
Female Skin Neoplasms Carcinoma, Basal Cell Carcinoma, Squamous Cell Reproducibility of Results Humans Algorithms Head and Neck Neoplasms Prospective Studies Aged Longitudinal Studies Aged, 80 and over Keratosis, Seborrheic Male Keratosis, Actinic Middle Aged Cheilitis Deep Learning
View on PubMed DOI

Deep learning-assisted multispectral imaging for early screening of skin diseases.

Photodiagnosis and photodynamic therapy Jul 26, 2024
INTRODUCTION: Melanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This proces...
Humans Skin Neoplasms Dermoscopy Deep Learning Psoriasis Nevus, Pigmented Skin Diseases Early Diagnosis Keratosis, Seborrheic Warts
View on PubMed DOI

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...
Machine Learning Algorithms Research Melanoma Skin Neoplasms Humans Neural Networks, Computer Artificial Intelligence Diagnostic Tests, Routine Observer Variation Pathology Nevus Keratosis, Seborrheic Carcinoma, Basal Cell Deep Learning Diagnosis, Differential Dermatology
View on PubMed DOI

A deep learning system for differential diagnosis of skin diseases.

Nature medicine May 18, 2020
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of sk...
Asian Photography Nurse Practitioners Keratosis, Seborrheic Warts Native Hawaiian or Pacific Islander Black or African American Eczema Acne Vulgaris Dermatitis, Seborrheic Folliculitis Psoriasis Diagnosis, Differential Dermatologists Skin Diseases Hispanic or Latino Telemedicine White People Humans Physicians, Primary Care Adult Female Alaska Natives Male Middle Aged Deep Learning Indians, North American Melanoma Skin Neoplasms Carcinoma, Basal Cell Carcinoma, Squamous Cell
View on PubMed DOI

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

Journal of the American Academy of Dermatology Jul 12, 2019
BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain.
Israel ROC Curve Internship and Residency United States Skin Neoplasms Colombia Humans Nevus Diagnosis, Differential Image Interpretation, Computer-Assisted Dermoscopy Melanoma Keratosis, Seborrheic Skin Spain Cross-Sectional Studies Dermatologists International Cooperation Deep Learning
View on PubMed DOI

Skin lesion classification with ensembles of deep convolutional neural networks.

Journal of biomedical informatics Aug 10, 2018
Skin cancer is a major public health problem with over 123,000 newly diagnosed cases worldwide in every year. Melanoma is the deadliest form of skin cancer, responsible for over 9000 deaths in the United States each year. Thus, reliable automatic mel...
Dermoscopy Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Nevus Keratosis, Seborrheic Melanocytes Machine Learning Algorithms Databases, Factual Melanoma Skin Neoplasms Humans Neural Networks, Computer
View on PubMed DOI

Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Keratosis, Actinic Middle Aged Lentigo Humans Deep Learning Software False Positive Reactions ROC Curve Female Predictive Value of Tests Photography Image Processing, Computer-Assisted Aged, 80 and over Skin Neoplasms Area Under Curve Diagnosis, Differential Young Adult Aged Keratosis, Seborrheic Biopsy Adult Warts Skin Male Granuloma, Pyogenic Datasets as Topic
View on PubMed DOI

Dermatologist-level classification of skin cancer with deep neural networks.

Nature Jan 25, 2017
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...
Photography Reproducibility of Results Humans Cell Phone Dermatologists Neural Networks, Computer Nevus Keratinocytes Melanoma Keratosis, Seborrheic Datasets as Topic Skin Neoplasms Automation
View on PubMed DOI
Popular Topics
Recent Journals