AIMC Topic: ROC Curve
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Plasminogen activator inhibitor-1 is associated with the metabolism and development of advanced colonic polyps.
Translational research : the journal of laboratory and clinical medicine
Jun 6, 2018
Implications of plasminogen activator inhibitor-1 (PAI-1) in colonic polyps remain elusive. A prospective study was conducted with 188 consecutive subjects who underwent colonoscopy at a tertiary referral center. Biochemical parameters, serum PAI-1 l...
A Deep Learning-Based Algorithm Identifies Glaucomatous Discs Using Monoscopic Fundus Photographs.
Ophthalmology. Glaucoma
Jun 5, 2018
PURPOSE: To develop and test the performance of a deep learning-based algorithm for glaucomatous disc identification using monoscopic fundus photographs.
diploS/HIC: An Updated Approach to Classifying Selective Sweeps.
G3 (Bethesda, Md.)
May 31, 2018
Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective s...
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.
BMC cancer
May 30, 2018
BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. Howev...
Receptors, Estrogen
Staining and Labeling
Predictive Value of Tests
Principal Component Analysis
Neoplasm Staging
Humans
Models, Biological
Prognosis
Breast Neoplasms
Supervised Machine Learning
Female
Middle Aged
Genetic Testing
Cell Nucleus
Risk Factors
ROC Curve
Breast
Aged
Image Processing, Computer-Assisted
Young Adult
Adult
Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.
Computer methods and programs in biomedicine
May 29, 2018
BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in the formulation of an effective and efficient strategy to improve the participation rate has been growing. The aim ...
Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.
Surgical innovation
May 29, 2018
BACKGROUND: A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a R...
Concussion classification via deep learning using whole-brain white matter fiber strains.
PloS one
May 24, 2018
Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses exp...
Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder.
Biomedical engineering online
May 23, 2018
OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, hig...
Machine learning in the integration of simple variables for identifying patients with myocardial ischemia.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
May 22, 2018
BACKGROUND: A significant number of variables are obtained when characterizing patients suspected with myocardial ischemia or at risk of MACE. Guidelines typically use a handful of them to support further workup or therapeutic decisions. However, it ...
Development of machine learning models to predict inhibition of 3-dehydroquinate dehydratase.
Chemical biology & drug design
May 18, 2018
In this study, we describe the development of new machine learning models to predict inhibition of the enzyme 3-dehydroquinate dehydratase (DHQD). This enzyme is the third step of the shikimate pathway and is responsible for the synthesis of chorisma...
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