PURPOSE: To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs.
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).
BACKGROUND: Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.
Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
Feb 20, 2018
OBJECTIVE: Sudden sensorineural hearing loss (SSHL) is a multifactorial disorder with high heterogeneity, thus the outcomes vary widely. This study aimed to develop predictive models based on four machine learning methods for SSHL, identifying the be...
Electronic health records (EHRs) contain critical information useful for clinical studies. Early assessment of patients' mortality in intensive care units is of great importance. In this paper, a Deep Rule-Based Fuzzy System (DRBFS) was proposed to d...
BACKGROUND: The available antibiotic decision-making systems were developed from a physician's perspective. However, because infectious diseases are common, many patients desire access to knowledge via a search engine. Although the use of antibiotics...
The Journal of investigative dermatology
Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Machine learning (ML) algorithms have proven highly accurate for identifying Randomized Controlled Trials (RCTs) but are not used much in practice, in part because the best way to make use of the technology in a typical workflow is unclear. In this w...
BACKGROUND: The correct determination of protein-protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been ...
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