PURPOSE: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the diagnosis of ductal carcinoma in situ (DCIS) by core needle biopsy.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Oct 16, 2019
OBJECT: Ischemic stroke readmission within 90 days of hospital discharge is an important quality of care metric. The readmission rates of ischemic stroke patients are usually higher than those of patients with other chronic diseases. Our aim was to i...
Recently, researchers in the area of biosensor based human emotion recognition have used different types of machine learning models for recognizing human emotions. However, most of them still lack the ability to recognize human emotions with higher c...
To improve the accuracy and robustness of hand-eye calibration, a hand-eye calibration method based on Schur matric decomposition is proposed in this paper. The accuracy of these methods strongly depends on the quality of observation data. Therefore,...
Machine learning techniques combined with wearable electronics can deliver accurate short-term blood glucose level prediction models. These models can learn personalized glucose-insulin dynamics based on the sensor data collected by monitoring severa...
BACKGROUND: Although geriatric depression is prevalent, diagnosis using self-reporting instruments has limitations when measuring the depressed mood of older adults in a community setting. Ecological momentary assessment (EMA) by using wearable devic...
In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus making active motion management an essential step in thoracic and abdominal tumor treatment. In curr...
BACKGROUND: The differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In recent years, artificial intelligence (AI) machine learning algorithms have started being used to an increasing extent in disease diagnosis due to the hig...
OBJECTIVE: Learning the structures and unknown correlations of a motor imagery electroencephalogram (MI-EEG) signal is important for its classification. It is also a major challenge to obtain good classification accuracy from the increased number of ...
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