AIMC Topic: Skin Neoplasms
Clear Filters Showing 471 to 480 of 515 articles
Identification of Potential Drug Therapy for Dermatofibrosarcoma Protuberans with Bioinformatics and Deep Learning Technology.
Current computer-aided drug design
Jan 1, 2022
BACKGROUND: Dermatofibrosarcoma protuberans (DFSP) is a rare mesenchymal tumor that is primarily treated with surgery. Targeted therapy is a promising approach to help reduce the high rate of recurrence. This study aims to identify the potential targ...
The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population.
Melanoma research
Dec 1, 2021
Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestim...
Machine learning for the identification of decision boundaries during the transition from radial to vertical growth phase superficial spreading melanomas.
Melanoma research
Dec 1, 2021
The objective of this study was to compute threshold values for the diameter of superficial spreading melanomas (SSMs) at which the radial growth phase (RGP) evolves into an invasive vertical growth phase (VGP). We examined reports from 1995 to 2019 ...
Novel strategy for applying hierarchical density-based spatial clustering of applications with noise towards spectroscopic analysis and detection of melanocytic lesions.
Melanoma research
Dec 1, 2021
Advancements in dermoscopy techniques have elucidated identifiable characteristics of melanoma which revolve around the asymmetrical constitution of melanocytic lesions consequent of unfettered proliferative growth as a malignant lesion. This study e...
Melanoma Skin Cancer Detection Using Recent Deep Learning Models.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Melanoma is considered as one of the world's deadly cancers. This type of skin cancer will spread to other areas of the body if not detected at an early stage. Convolutional Neural Network (CNN) based classifiers are currently considered one of the m...
XGSEA: CROSS-species gene set enrichment analysis via domain adaptation.
Briefings in bioinformatics
Sep 2, 2021
MOTIVATION: Gene set enrichment analysis (GSEA) has been widely used to identify gene sets with statistically significant difference between cases and controls against a large gene set. GSEA needs both phenotype labels and expression of genes. Howeve...
Interest in artificial intelligence for the diagnosis of non-melanoma skin cancer: a survey among French general practitioners.
European journal of dermatology : EJD
Aug 1, 2021
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cancer is frequent and difficult to diagnose. We aimed to assess whether GPs are facing difficulties in diagnosing non-pigmented skin tumours (NPSTs) and w...
The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.
American journal of clinical dermatology
Mar 1, 2021
Artificial intelligence (AI) algorithms have been shown to diagnose skin lesions with impressive accuracy in experimental settings. The majority of the literature to date has compared AI and dermatologists as opponents in skin cancer diagnosis. Howev...
Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images.
Science translational medicine
Feb 17, 2021
A reported 96,480 people were diagnosed with melanoma in the United States in 2019, leading to 7230 reported deaths. Early-stage identification of suspicious pigmented lesions (SPLs) in primary care settings can lead to improved melanoma prognosis an...
Deep learning with transfer learning in pathology. Case study: classification of basal cell carcinoma.
Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
Jan 1, 2021
Establishing basal cell carcinoma (BCC) subtype is sometimes challenging for pathologists. Deep-learning (DL) algorithms are an emerging approach in image classification due to their performance, accompanied by a new concept - transfer learning, whic...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32523
- Neural Networks, Computer 30491
- Algorithms 27737
- Deep Learning 27290
- Artificial Intelligence 25212
- Robotics 13430
- Image Processing, Computer-Assisted 9887
- Retrospective Studies 9532
- Magnetic Resonance Imaging 6482
- Reproducibility of Results 5745
- Tomography, X-Ray Computed 4959
- Support Vector Machine 4812
- Computational Biology 4396
- Brain 4188
- Computer Simulation 3963
Recent Journals
- Scientific reports 7012
- Sensors (Basel, Switzerland) 4794
- PloS one 4303
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2040
- Computational intelligence and neuroscience 1931
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
- IEEE journal of biomedical and health informatics 1195
- Journal of chemical information and modeling 1087
- Nature communications 1071
- Computer methods and programs in biomedicine 895
- Bioinformatics (Oxford, England) 879
- Journal of medical Internet research 878
- IEEE transactions on neural networks and learning systems 859