An integrated physical diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) substrate. This DONN has compact structure and can realize the function of machine learning with whole-passive fully-optical m...
The application of computer-based technology to surgery has the potential to enhance the accuracy and outcomes of surgical procedures and perioperative care. Such innovative technologies include the integration of artificial intelligence into surgica...
Studies in health technology and informatics
Sep 21, 2021
Expert systems have a long tradition in both medical informatics and artificial intelligence research. Traditionally, such systems are created by implementing knowledge provided by experts in a system that can be queried for answers. To automatically...
Studies in health technology and informatics
Sep 21, 2021
In this paper a machine learning model for automatic detection of abnormalities in electroencephalography (EEG) is dissected into parts, so that the influence of each part on the classification accuracy score can be examined. The most successful setu...
A solution of spectroscopic inverse problems, implying determination of target parameters of the research object via analysis of spectra of various origins, is an overly complex task, especially in case of strong variability of the research object. O...
N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based appr...
Journal of the American Medical Informatics Association : JAMIA
Sep 18, 2021
OBJECTIVE: The study sought to determine whether machine learning can predict initial inpatient total daily dose (TDD) of insulin from electronic health records more accurately than existing guideline-based dosing recommendations.
Journal of the American Medical Informatics Association : JAMIA
Sep 18, 2021
OBJECTIVE: We propose an interpretable disease prediction model that efficiently fuses multiple types of patient records using a self-attentive fusion encoder. We assessed the model performance in predicting cardiovascular disease events, given the r...
BACKGROUND: Populational ageing has been increasing in a remarkable rate in developing countries. In this scenario, preventive strategies could help to decrease the burden of higher demands for healthcare services. Machine learning algorithms have be...
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