Skin Cancer

Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent years. Most of the existing methods assume that the cost of intervention at each state and time point, referred to as the immediate cost function, is fully known. In this paper, we employ the Partially-Observed Boolean Dynamical System (POBDS) signal m...

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 results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the hands and feet and evaluated its usefulness for the early diagnosis of these conditions.

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-cell receptors, the immune repertoire. The interr...

Machine learning-based diagnosis of melanoma using macro images.

Cancer bears a poisoning threat to human society. Melanoma, the skin cancer, originates from skin layers and penetrates deep into subcutaneous layers....

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 described for diagnosing a wide variety of cancers...

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-basal cell carcinoma, squamous cell carcinoma, intr...

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 development of non-melanoma skin cancer (NMSC). The ...

Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks.

Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diagnosis of melanoma. However, this task is challengi...

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 using an environmentally friendly method and to c...

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 cell metastasis. High expression levels of CD44 corr...

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 metastasis and initiation of melanoma. Therefore, sele...

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 fastest-growing cancers. Early diagnosis and treatment ...

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 amino acid change. However, integrated germline and so...

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 inhibitors are important for their potential application in...

and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer i...

An expert system for selecting wart treatment method.

As benign tumors, warts are made through the mediation of Human Papillomavirus (HPV) and may grow on all parts of body, especially hands and feet. The...

Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.

We develop a novel method for classifying melanocytic tumors as benign or malignant by the analysis of digital dermoscopy images. The algorithm follow...

Growth of Uveal Melanoma following Intravitreal Bevacizumab.

PURPOSE: Typically treatment of large melanomas (by Collaborative Ocular Melanoma Study criteria) is restricted to enucleation, due to size constraint...

High Interleukin 27 Production is Associated with Early Clinical Stage and Localized Disease in Patients with Melanoma.

BACKGROUND: The immune response in patients with melanoma is an important focus of research due to the tumor's resistance and immunotherapy possibilit...