Dermatology

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 years because of the advent of antibodies targeting programmed cell death protein-1 (PD1). However, the response rate is ~40% and baseline biomarkers for the outcome are yet to be identified. Here, we aimed to determine whether artificial intelligence might be useful in weighting the importance of basel...

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 research. Most data points are stored in semistructured or unstructured legacy documents and require manual data abstraction into a structured format to render the information more readily accessible, searchable, and generally analysis ready. The substantial labor needed for this can be cost prohibit...

Selection of Radiomics Features based on their Reproducibility.

Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications with Small Sample Size (SSS) unbalanced datasets. Exi...

Boundary-aware Semi-supervised Deep Learning for Breast Ultrasound Computer-Aided Diagnosis.

Breast ultrasound (US) is an effective imaging modality for breast cancer diagnosis. US computer-aided diagnosis (CAD) systems have been developed for...

Light Field Image Dataset of Skin Lesions.

Light field imaging technology has been attracting increasing interest because it enables capturing enriched visual information and expands the proces...

Deep Learning for Automating the Organization of Institutional Dermatology Image Stores.

A common challenge faced by researchers associated with healthcare institutions is that data of interest are often contained in electronic medical inf...

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 reflectance confocal microscopy (RCM) mosaics. Skin ...

Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT.

PURPOSE: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial ...

Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic lymphoma kinase () mutation tests. To facilitate ...

Computational neural network in melanocytic lesions diagnosis: artificial intelligence to improve diagnosis in dermatology?

Diagnosis in dermatology is largely based on contextual factors going far beyond the visual and dermoscopic inspection of a lesion. Diagnostic tools s...

Using Neural Networks for Diagnosing in Dermatology.

The paper deals with neural networks for decision support in diagnosing in dermatology. There were several iterations during development. We classifie...

[A real-world study of paritaprevir/ritonavir-ombitasvir combined with dasabuvir in the treatment of genotype 1b chronic hepatitis C].

To recognize the efficacy and safety of paritaprevir/ritonavir-ombitasvir combined with dasabuvir (OBV/PTV/RTV+DSV) in the treatment of genotype 1b c...

[A Surgical Case of AFP-Producing Gastric Cancer Discovered by Rupture of Liver Metastatic Lesion].

A 57-year-old man visited our hospital with right hypochondralgia. Abdominal contrast CT showed a 10 cm sized mass in S6-7of the liver and abdominal h...

Serum Concentrations of Interferon Gamma (IFN-γ) in Patients with Psoriasis: Correlation with Clinical Type and Severity of the Disease.

INTRODUCTION: The etiopathogenesis of psoriasis is still unclear but there is evidence that many of cytokines released by keratinocytes and inflammato...

A machine learning approach for somatic mutation discovery.

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. T...

Artificial Intelligence for the Objective Evaluation of Acne Investigator Global Assessment.

INTRODUCTION: The evaluation of Acne using ordinal scales reflects the clinical perception of severity but has shown low reproducibility both intra- a...

Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can im...

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 data comparing a CNN's diagnostic performance to ...

False-positive Troponin I Assay elevation due to occult Mixed Cryoglobulinemic Vasculitis.

A 53-year-old man with active hepatitis C and cirrhosis presented with a vasculitic rash, myalgias, and fatigue, and was found to have an elevated car...

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a d...