Skin Cancer

Multimodal skin lesion classification using deep learning.

While convolutional neural networks (CNNs) have successfully been applied for skin lesion classifica...

Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.

PURPOSE: To evaluate performance and the clinical impact of a novel machine learning based vessel-su...

Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features.

In this paper, we present a novel framework for dermoscopy image recognition via both a deep learnin...

Skin lesion classification with ensembles of deep convolutional neural networks.

Skin cancer is a major public health problem with over 123,000 newly diagnosed cases worldwide in ev...

Machine learning model in melanoma.

Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features.

The presence of certain clinical dermoscopic features within a skin lesion may indicate melanoma, an...

Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desir...

Acral melanoma detection using a convolutional neural network for dermoscopy images.

BACKGROUND/PURPOSE: Acral melanoma is the most common type of melanoma in Asians, and usually result...

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.

The adaptive immune system recognizes antigens an immense array of antigen-binding antibodies and T...

Machine learning-based diagnosis of melanoma using macro images.

Cancer bears a poisoning threat to human society. Melanoma, the skin cancer, originates from skin la...

SetSVM: An Approach to Set Classification in Nuclei-Based Cancer Detection.

Due to the importance of nuclear structure in cancer diagnosis, several predictive models have been ...

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

We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-b...

Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the de...

Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks.

Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diag...

Antibacterial, Antiproliferative, and Immunomodulatory Activity of Silver Nanoparticles Synthesized with Fucans from the Alga Dictyota mertensii.

In this study, we aimed to synthesize silver nanoparticles containing fucans from (Martius) Kützing...

Effect of dacarbazine on CD44 in live melanoma cells as measured by atomic force microscopy-based nanoscopy.

CD44 ligand-receptor interactions are known to be involved in regulating cell migration and tumor ce...

Salinomycin-loaded lipid-polymer nanoparticles with anti-CD20 aptamers selectively suppress human CD20+ melanoma stem cells.

Melanoma is the deadliest type of skin cancer. CD20+ melanoma stem cells (CSCs) are pivotal for meta...

Melanoma segmentation based on deep learning.

Malignant melanoma is one of the most deadly forms of skin cancer, which is one of the world's faste...

Machine learning and melanoma: The future of screening.

Identification of potentially oncogenic alterations from tumor-only samples reveals Fanconi anemia pathway mutations in bladder carcinomas.

Cancer is caused by germline and somatic mutations, which can share biological features such as amin...

Effects of protein hydrolysate from chicken feather meal on tyrosinase activity and melanin formation in B16F10 murine melanoma cells.

Tyrosinase is a copper-containing enzyme that controls mammalian melanogenesis. Tyrosinase inhibitor...