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1.发明申请公开(公告)号：US20170147753A1
公开(公告)日：2017-05-25
申请号：US15349703
申请日：2016-11-11
Inventor： Youngwoong HAN , Ho-Youl JUNG , Jae Hun CHOI , Minho KIM , YoungWon KIM , Myung-eun LIM , Dae Hee KIM , Seunghwan KIM
CPC classification number: G16H10/60 , G06F16/285 , G06F16/9535 , G06N5/022 , G06N20/00 , G16H50/50 , G16H50/70
Abstract: Provided are a search method and device in which, in order to search for health data having a multivariate (multi-dimensional) time-series characteristic with high calculation complexity for a search, a format of the health data is converted and a dimension of the health data is reduced through feature extraction to which a learning model is applied, so that the calculation complexity for the search may be remarkably reduced and the similar case search may be performed efficiently.
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公开(公告)号：US20150199476A1
公开(公告)日：2015-07-16
申请号：US14597052
申请日：2015-01-14
Inventor： Minho KIM , Dae Hee KIM , Myung-eun LIM , Ho-Youl JUNG
IPC: G06F19/22
Abstract: Provided is a method for analyzing a genome by a genome analyzing device. The method of analyzing a genome of the present invention includes: reading sequencing data of the genome from a storage device; selecting a position to be analyzed among positions corresponding to the sequencing data; and determining a base type at the selected position by using base types and quality values of bases corresponding to the selected position among the sequencing data.
Abstract translation: 提供了一种通过基因组分析装置分析基因组的方法。 分析本发明的基因组的方法包括：从存储装置读取基因组的测序数据; 在与排序数据相对应的位置中选择要分析的位置; 以及通过使用与所述排序数据中的所选择的位置相对应的碱基的碱基类型和质量值来确定所选位置处的碱基类型。
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3.发明申请公开(公告)号：US20180150608A1
公开(公告)日：2018-05-31
申请号：US15808476
申请日：2017-11-09
Inventor： Dae Hee KIM , Minho KIM , YoungWon KIM , Donghun LEE , Myung-eun LIM , Ho-Youl JUNG , Jae Hun CHOI , Youngwoong HAN
CPC classification number: G16H50/20 , G06N20/00 , G16B5/00 , G16B20/00 , G16B40/00 , G16H40/67 , G16H50/50 , G16H50/70
Abstract: Provided are a device and method for diagnosing cardiovascular disease for providing rapid and accurate treatment and prescription for cardiovascular disease by accurately performing a diagnosis of cardiovascular disease for a particular user using the user's personal health checkup data and genome information measured periodically and the target gene of cardiovascular disease.
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4.发明申请公开(公告)号：US20170357760A1
公开(公告)日：2017-12-14
申请号：US15365834
申请日：2016-11-30
Inventor： Youngwoong HAN , Jae Hun CHOI , YoungWon KIM , Minho KIM , Myung-eun LIM , Ho-Youl JUNG , Donghun LEE , Dae Hee KIM
Abstract: Provided are a clinical decision supporting ensemble system and method. Clinical prediction results for a patient obtained through machine learning and received from a plurality of external medical institutions are integrated to perform an ensemble prediction, so that not only a current condition of the patient but also a future process of an illness of the patient is predicted to assist a medical person in making a quick and correct medical decision.
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5.发明申请公开(公告)号：US20180150609A1
公开(公告)日：2018-05-31
申请号：US15812540
申请日：2017-11-14
Inventor： Minho KIM , YoungWon KIM , Donghun LEE , Jae Hun CHOI , Dae Hee KIM , Myung-eun LIM , Ho-Youl JUNG , Youngwoong HAN , Seunghwan KIM
CPC classification number: G16H50/20 , G06N3/04 , G06N5/048 , G06N20/00 , G16H10/60 , G16H50/50 , Y02A90/26
Abstract: The present disclosure herein relates to a future health trend forecasting system and a method thereof through a similar case cluster-based prediction model, and more specifically, to a server and a method thereof for extracting multiple associated feature similar case clusters that match a prediction query for the user's health information through a class prediction model and a future value prediction model for health features of a similar case cluster generated by cyclically clustering the target feature that is a health feature for personal health information and an associated feature of the target feature, predicting future health trends for each associated feature using multiple prediction models based on corresponding similar case clusters, and combining and outputting the prediction results.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20150261990A1
公开(公告)日：2015-09-17
申请号：US14480216
申请日：2014-09-08
Inventor： Dae Hee KIM , Ho Youl JUNG , Min Ho KIM , Myung Eun LIM , Jae Hun CHOI
CPC classification number: H03M7/70 , G06T9/00 , G06T2207/30072 , H03M7/40
Abstract: Provided are a method and apparatus for compressing DNA data based on a binary image. The method for compressing DNA data based on a binary image includes splitting DNA data including adenine (A), thymine (T), guanine (G), cytosine (C), and an indefinite base (N) into a plurality of binary images, determining a coding mode of each of the binary images according to characteristics of each of the binary images, and first coding each of the binary images based on the determined coding mode.
Abstract translation: 提供了一种基于二进制图像压缩DNA数据的方法和装置。 基于二值图像压缩DNA数据的方法包括将包括腺嘌呤（A），胸腺嘧啶（T），鸟嘌呤（G），胞嘧啶（C））和不定碱（N）的DNA数据分解成多个二值图像， 根据每个二进制图像的特性确定每个二进制图像的编码模式，并且基于所确定的编码模式对每个二进制图像进行编码。
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公开(公告)号：US20240013539A1
公开(公告)日：2024-01-11
申请号：US18215925
申请日：2023-06-29
Inventor： SEONGHUN SEO , Dae Hee KIM
IPC: G06V20/50 , G06V10/774 , G06V10/82 , G06T7/60 , B65G43/00
CPC classification number: G06V20/50 , G06V10/774 , G06V10/82 , G06T7/60 , B65G43/00 , B65G2203/041
Abstract: Disclosed are an insertion automation method and system based on deep-learning parcel recognition. The insertion automation method includes determining an initial gradient change angular velocity of a tipper based on a total weight of parcels in the tipper, recognizing a loading state of the parcels in the tipper by inputting images of the parcels in the tipper to an object recognition model, and redetermining a gradient change angular velocity and gradient angle of the tipper based on the recognized loading state, in which the loading state of the parcels in the tipper includes at least one of a position, size, and packing material of the parcels in the tipper.
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公开(公告)号：US20180151254A1
公开(公告)日：2018-05-31
申请号：US15828180
申请日：2017-11-30
Inventor： Youngwoong HAN , Ho-Youl JUNG , Jae Hun CHOI , Dae Hee KIM , Minho KIM , Seunghwan KIM , YoungWon KIM , Donghun LEE , Myung-Eun LIM
CPC classification number: G16H10/60 , G06F16/2465 , G06F16/283 , G06F2216/03 , G06K9/6218 , G06K9/6232 , G06K9/6247 , G06K9/6271 , G06N3/08 , G06N20/00 , G16H50/20 , G16H50/70
Abstract: Provided are a search method and device for searching for a case similar to user's health data at high-speed from large scale multi-dimensional time series health data. The method includes preprocessing health data inputted through an interface circuit, performing a multi-dimensional feature extraction learning based on machine learning on the preprocessed health data, and generating one or more feature extraction models for dimension reduction based on the multi-dimensional feature extraction learning.
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9.发明申请公开(公告)号：US20170147777A1
公开(公告)日：2017-05-25
申请号：US15353671
申请日：2016-11-16
Inventor： YoungWon KIM , Minho KIM , Jae Hun CHOI , Myung-eun LIM , Ho-Youl JUNG , Youngwoong HAN , Dae Hee KIM , Seunghwan KIM
Abstract: The inventive concept relates to a method and apparatus for predicting health data values through the generation of a health data pattern. The inventive concept provides a health data value prediction method and apparatus. The health data value prediction method and apparatus may select health data values and important health characteristics associated with the health data values from big data on a plurality of pieces of time-series health information. The health data value prediction method and apparatus may form a health data value prediction model that has repetitively learned the pattern, and accurately predict a user's health data value through the prediction model.
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公开(公告)号：US20170147755A1
公开(公告)日：2017-05-25
申请号：US15360913
申请日：2016-11-23
Inventor： Myung-eun LIM , Jae Hun CHOI , Minho KIM , YoungWon KIM , Ho-Youl JUNG , Youngwoong HAN , Dae Hee KIM , Seunghwan KIM
CPC classification number: G16H10/60 , H04L63/08 , H04L63/083
Abstract: Provided are a personal cloud based personal health record management method and device for allowing users to dominantly manage personal health records, which are accumulated and managed by each of various health service institutions, through a personal health record management device and a personal cloud repository.
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