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公开(公告)号:GB2583309A
公开(公告)日:2020-10-21
申请号:GB202010618
申请日:2018-12-06
Applicant: IBM
Inventor: TIM RUMBELL , JAMES KOZLOSKI
Abstract: A computer-implemented method for generating neuronal models for personalized drug treatment selection for a patient includes receiving allelic information for at least one neurophysiological coding region of a genome of the patient, and a physiological model of a disease associated with the genome. The method further includes determining a set of ion channels correlated with the allelic information, and receiving a set of phenotypic measurement ranges associated with the ion channels from the determined set. The method further includes performing a simulation to generate multiple neuronal models comprising the set of ion channels with parameter values within the corresponding phenotypic measurement ranges, and analyzing the generated neuronal models to identify components that affect the physiological model. The method further includes selecting a drug for the patient based at least in part on the identified components.
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公开(公告)号:GB2605335A
公开(公告)日:2022-09-28
申请号:GB202209099
申请日:2020-11-30
Applicant: IBM
Inventor: JAMES KOZLOSKI , SARBAJIT RAKSHIT , MICHAEL GORDON , KOMMINIST WELDEMARIAM
Abstract: A method for predictively reconstructing a physical event using augmented reality, comprising: identifying relative states of objects located in a physical area by using video analysis to analyze collected video feeds from the physical event before and after a physical event involving at least one of the objects, creating a knowledge corpus including the video analysis and the collected video feeds associated with the physical event and historical information, and capturing data, by a computing device, of the physical event area, identifying possible precursor events based on the captured data and the knowledge corpus, and generating a virtual reconstruction of the physical event using the possible precursor events, displaying, by the computer device, the generated virtual reconstruction of the predicted physical event, wherein the displayed virtual reconstruction of the predicted physical event overlays an image of the physical event area.
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