Disability and rehabilitation. Assistive technology
Jul 8, 2019
To define semi-supervised machine learning (SSML) and explore current and potential applications of this analytic strategy in rehabilitation research. We conducted a scoping review using PubMed, GoogleScholar and Medline. Studies were included if th...
Hemolytic toxicity of small molecules, as one of the important ADMET end points, can cause the lysis of erythrocytes membrane and leaking of hemoglobin into the blood plasma, which leads to various side effects. Thus, it is very crucial to assess the...
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many different 2D medical image analysis tasks. In clinical practice, however, a large part of the medical imaging data available is in 3D, e.g, magnetic resonance ima...
Cellular frustrated models have been developed to describe how the adaptive immune system works. They are composed by independent agents that continuously pair and unpair depending on the information that one sub-set of these agents display. The emer...
Accurate medical disease diagnosis is considered to be an important classification problem. The main goal of the classification process is to determine the class to which a certain pattern belongs. In this article, a new classification technique base...
Computational intelligence and neuroscience
Jul 7, 2019
The use of intelligent judgment technology to assist in judgment is an inevitable trend in the development of judgment in contemporary social legal cases. Using big data and artificial intelligence technology to accurately determine multiple accusati...
International journal of medical informatics
Jul 6, 2019
OBJECTIVE: Electronic health record (EHR) systems contain structured data (such as diagnostic codes) and unstructured data (clinical documentation). Clinical insights can be derived from analyzing both. The use of natural language processing (NLP) al...
An integrated approach is proposed across visual and textual data to both determine and justify a medical diagnosis by a neural network. As deep learning techniques improve, interest grows to apply them in medical applications. To enable a transition...
The annihilating filter-based low-rank Hankel matrix approach (ALOHA) is one of the state-of-the-art compressed sensing approaches that directly interpolates the missing k -space data using low-rank Hankel matrix completion. The success of ALOHA is d...
Epidemiologists use prediction models to downscale (i.e., interpolate) air pollution exposure where monitoring data is insufficient. This study compares machine learning prediction models for ground-level ozone during wildfires, evaluating the predic...
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