APPARATUS AND METHODS FOR MACHINE LEARNING TO IDENTIFY AND DIAGNOSE INTRACRANIAL HEMORRHAGES

    公开(公告)号:US20230132247A1

    公开(公告)日:2023-04-27

    申请号:US17508993

    申请日:2021-10-23

    Abstract: In some embodiments, an apparatus includes providing a representation of a set of digital medical images to a first machine learning model to define a feature vector associated with a presence of an intracranial hemorrhage. A representation of the set of digital medical images is provided to a second machine learning model to define a second feature vector associated with a volume of the intracranial hemorrhage. Using a third machine learning model, a set of EMRs associated with risk factors for a predefined indication is analyzed to define a third feature vector. The first, second and third feature vectors are provided as inputs to a fourth machine learning model to determine a metric associated with an applicability of a specific treatment associated with a predefined indication. An alert is sent to relevant healthcare providers and relevant tests, procedures or bloodwork are ordered for the predefined indication.

    System for elliptic curve encryption using multiple points on an elliptic curve derived from scalar multiplication
    8.
    发明授权
    System for elliptic curve encryption using multiple points on an elliptic curve derived from scalar multiplication 失效
    使用从标量乘法导出的椭圆曲线上的多个点进行椭圆曲线加密的系统

    公开(公告)号:US07680270B2

    公开(公告)日:2010-03-16

    申请号:US10532696

    申请日:2003-10-20

    CPC classification number: G06F7/725 H04L9/3066 H04L2209/08 H04L2209/16

    Abstract: A method of elliptic curve encryption includes, (a) selecting an elliptic curve Ep (a,b) of the form y2=x3+ax+b mod (p) wherein a and b are non-negative integers less than p satisfying the formula 4 a3+27b2 mod (p) not equal to 0; (b) generating a large 160 bit random number by a method of concatenation of a number of smaller random numbers; (c) generating a well hidden point G (x,y) on the elliptic curve Ep (a,b) by scalar multiplication of a point B (x,y) on the elliptic curve with a large random integer which further includes the steps: (i) converting the large random integer into a series of powers of 231; (ii) converting each coefficient of 231 obtained from above step into a binary series; (iii) multiplication of binary series obtained from steps (i) and (ii) above with the point B (x,y) on the elliptic curve; (d) generating a private key nA (of about >=160 bit length); (e) generating a public key PA (x,y) given by the formula PA (x,y)=(nA−G (x,y)) mod (p); (f) encrypting the input message MSG; (g) decrypting the ciphered text.

    Abstract translation: 椭圆曲线加密的方法包括:(a)选择形式为y2 = x3 + ax + bmod(p)的椭圆曲线Ep(a,b),其中a和b是小于p的非负整数,满足公式 4 a3 + 27b2 mod(p)不等于0; (b)通过串联较小的随机数的方法产生大的160位随机数; (c)通过椭圆曲线上的点B(x,y)与大的随机整数进行标量乘积,在椭圆曲线Ep(a,b)上产生良好的隐藏点G(x,y),其进一步包括步骤 :(i)将大随机整数转换为231的一系列幂; (ii)将从上述步骤获得的每个系数231转换成二进制序列; (iii)从上述步骤(i)和(ii)获得的二进制序列与椭圆曲线上的点B(x,y)的乘法; (d)产生私钥nA(约> = 160位长度); (e)产生由公式PA(x,y)=(nA-G(x,y))mod(p)给出的公钥PA(x,y); (f)加密输入消息MSG; (g)解密加密文本。

    Electromagnetic detection of an embedded dielectric region within an
ambient dielectric region

    公开(公告)号:US6064903A

    公开(公告)日:2000-05-16

    申请号:US221337

    申请日:1998-12-28

    CPC classification number: G06K9/0057 A61B5/05 A61B5/0507

    Abstract: A system for and method of electromagnetically detecting an embedded dielectric region within a target object are provided. The method includes the steps of: (i) selecting a target object including a plurality of discrete scattering mediums, wherein the plurality of discrete scattering mediums include the embedded dielectric region and an adjacent dielectric region, and wherein the plurality of discrete scattering mediums define at least one dielectric interface between the embedded dielectric region and the adjacent dielectric region; (ii) directing electromagnetic radiation at the target object, wherein the electromagnetic radiation is characterized by a diagnostic frequency that is varied incrementally over a diagnostic frequency band; (iii) detecting electromagnetic radiation reflected by the target object over the predetermined frequency band such that there are M measurements of a reflected electromagnetic signal at frequencies f.sub.1, f.sub.2, . . . , f.sub.N, where M represents a number of scattering mediums within the target object and where N represents a number of diagnostic frequencies within the diagnostic frequency band; (iv) constructing a correlation matrix representative of the reflected signal, wherein the correlation matrix comprises a number of signal eigenvectors and a number of noise eigenvectors; (v) decorrelating the correlation matrix by dividing the reflected signal according to frequency sub-bands within the diagnostic frequency band, wherein adjacent bands of the frequency sub-bands overlap, forming a series of iterated correlation matrices using signal eigenvectors and noise eigenvectors from each of the overlapping frequency sub-bands, forming a decorrelated matrix by averaging the iterated correlation matrices, wherein the decorrelated matrix comprises a finite group of signal eigenvectors and a finite group of noise eigenvectors; and (vi) constructing a scattering signature of the target object from the finite group of signal eigenvectors, wherein the scattering signature is indicative of the properties of the embedded dielectric region and the adjacent dielectric region.

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