AIMC Topic: Humans
Showing 66961 to 66970 of 95995 articles
Multi-level features combined end-to-end learning for automated pathological grading of breast cancer on digital mammograms.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 13, 2018
We propose to discriminate the pathological grades directly on digital mammograms instead of pathological images. An end-to-end learning algorithm based on the combined multi-level features is proposed. Low-level features are extracted and selected b...
How Cognitive Machines Can Augment Medical Imaging.
AJR. American journal of roentgenology
Nov 13, 2018
OBJECTIVE: Artificial intelligence (AI) neural networks rapidly convert disparate facts and data into highly predictive analytic models. Machine learning maps image-patient phenotype correlations opaque to standard statistics. Deep learning performs ...
Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network.
Sensors (Basel, Switzerland)
Nov 13, 2018
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations....
Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation.
PLoS medicine
Nov 13, 2018
BACKGROUND: Invasive fractional flow reserve (FFR) is a standard tool for identifying ischemia-producing coronary stenosis. However, in clinical practice, over 70% of treatment decisions still rely on visual estimation of angiographic stenosis, which...
Severity of Illness Index
Diagnosis, Computer-Assisted
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Machine Learning
Humans
Coronary Vessels
Prognosis
Retrospective Studies
Coronary Angiography
Clinical Decision-Making
Fractional Flow Reserve, Myocardial
Myocardial Ischemia
Ultrasonography, Interventional
Republic of Korea
Cardiac Catheterization
Female
Coronary Stenosis
Reproducibility of Results
Aged
Male
Middle Aged
Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth cohort.
PLoS medicine
Nov 13, 2018
BACKGROUND: The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because allergic sensitisation may not be a single ent...
Transforming health policy through machine learning.
PLoS medicine
Nov 13, 2018
In their Perspective, Ara Darzi and Hutan Ashrafian give us a tour of the future policymaker's machine learning toolkit.
Adaptive Neural Control of Underactuated Surface Vessels With Prescribed Performance Guarantees.
IEEE transactions on neural networks and learning systems
Nov 12, 2018
This paper presents adaptive neural tracking control of underactuated surface vessels with modeling uncertainties and time-varying external disturbances, where the tracking errors consisting of position and orientation errors are required to keep ins...
How can the presence of a surgical care practitioner improve training for staff who are learning how to scrub for robotics cases in a urology theatre?
Journal of perioperative practice
Nov 12, 2018
AIM: This study examines how a surgical care practitioner can contribute to the learning needs of junior scrub staff learning to scrub for urological robotics cases. Key themes include education, technical training, non-technical skills, patient safe...
Predicting chemo-brain in breast cancer survivors using multiple MRI features and machine-learning.
Magnetic resonance in medicine
Nov 12, 2018
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherapy drugs may result in brain damage during treatment. When a patient's brain is changed in response t...
The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review.
Journal of affective disorders
Nov 12, 2018
BACKGROUND: Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the existing literature on the application of machine learning techniques to predict self-injurious thought...
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