Stock price prediction is a challenging task, in which machine learning methods have recently been successfully used. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical indicators and quantitative analysis and te...
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Jun 11, 2020
Artificial intelligence (AI) is emerging as a key component in diagnostic medical imaging, including echocardiography. AI with deep learning has already been used with automated view labeling, measurements, and interpretation. As the development and ...
Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three in...
PURPOSE: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS).
OBJECTIVE: To evaluate machine learning-based classifiers in detecting clinically significant prostate cancer (PCa) with Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions.
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding ...
By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal-organic frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too m...
Journal of neuroengineering and rehabilitation
Jun 10, 2020
BACKGROUND: In clinical practice, therapists often rely on clinical outcome measures to quantify a patient's impairment and function. Predicting a patient's discharge outcome using baseline clinical information may help clinicians design more targete...
OBJECTIVE: The localization of origins of premature ventricular contraction (PVC) is the key factor for the success of ablation of ventricular arrhythmias. Existing methods rely heavily on manual extraction of PVC beats, which limits their applicatio...
HYPOTHESIS/PURPOSE: The objective is to develop and validate an artificial intelligence model, specifically an artificial neural network (ANN), to predict length of stay (LOS), discharge disposition, and inpatient charges for primary anatomic total (...
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