Skin Cancer

Role of Intralesional Vitamin D3 in the Treatment of Cutaneous Warts.

BACKGROUND: Cutaneous warts are common benign skin lesions caused by human papillomavirus. Various t...

Dermoscopic Features of Giant Molluscum Contagiosum in a Patient with Acquired Immunodeficiency Syndrome.

Giant molluscum contagiosum (MC) is a peculiar variant of the disease with the presence of multiple ...

Detection of Pathogenic Variants With Germline Genetic Testing Using Deep Learning vs Standard Methods in Patients With Prostate Cancer and Melanoma.

IMPORTANCE: Less than 10% of patients with cancer have detectable pathogenic germline alterations, w...

[Determination of dacarbazine in the urine of mice with melanoma by high performance liquid chromatography].

Dacarbazine (DTIC) is a first-line chemotherapy drug that is widely used in clinical practice for ma...

Deep learning-level melanoma detection by interpretable machine learning and imaging biomarker cues.

SIGNIFICANCE: Melanoma is a deadly cancer that physicians struggle to diagnose early because they la...

Prediction of immune checkpoint inhibition with immune oncology-related gene expression in gastrointestinal cancer using a machine learning classifier.

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of gastrointestina...

The value of convolutional neural networks in the diagnosis of melanoma simulators.

Adaptive back-stepping cancer control using Legendre polynomials.

Here, a model-free controller for cancer treatment is presented. The treatment objective is to find ...

Artificial intelligence for melanoma diagnosis: how can we deliver on the promise?

Artificial Intelligence Estimates the Importance of Baseline Factors in Predicting Response to Anti-PD1 in Metastatic Melanoma.

OBJECTIVE: Prognosis of patients with metastatic melanoma has dramatically improved over recent year...

Enhancing Case Capture, Quality, and Completeness of Primary Melanoma Pathology Records via Natural Language Processing.

PURPOSE: Medical records contain a wealth of useful, informative data points valuable for clinical r...

Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy.

We propose an approach based on a convolutional neural network to classify skin lesions using the re...

Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers.

INTRODUCTION: Immunotherapy is regarded as one of the major breakthroughs in cancer treatment. Despi...

Programmed cell death protein-1/programmed death-ligand 1 blockade enhances the antitumor efficacy of adoptive cell therapy against non-small cell lung cancer.

BACKGROUND: Cytokine-induced killer (CIK) cells and natural killer (NK) cells are employed by two di...

A machine learning approach for somatic mutation discovery.

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations an...

Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powe...

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

BACKGROUND: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but...

Enhancement of the Immune Function by Titanium Dioxide Nanorods and Their Application in Cancer Immunotherapy.

With the rapid development of nanotherapy, concerns surrounding the possible use of nanomaterials-me...

A deep bag-of-features model for the classification of melanomas in dermoscopy images.

Deep learning and unsupervised feature learning have received great attention in past years for thei...

Conceptual Knowledge Discovery in Databases for Drug Combinations Predictions in Malignant Melanoma.

The worldwide incidence of melanoma is rising faster than any other cancer, and prognosis for patien...

A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition.

Advanced techniques in machine learning combined with scalable "cloud" computing infrastructure are ...