Patents by Inventor Pierre Mahé

Pierre Mahé has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12091702
    Abstract: An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability ƒ(m) according to relation f ? ( m ) = pN ? ( m | ? , ? ) pN ? ( m | ? , ? ) + ( 1 - p ) ? N ? ( m | ? _ , ? _ ) where: m is the distance calculated for the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range fr
    Type: Grant
    Filed: December 9, 2019
    Date of Patent: September 17, 2024
    Assignee: BIOMERIEUX, INC.
    Inventors: Grégory Strubel, Maud Arsac, Denis Desseree, Pierre-Jean Cotte-Pattat, Pierre Mahe
  • Patent number: 11922959
    Abstract: A method and device for compressing audio signals forming, over time, a succession of sample frames, in each of N channels of an ambisonic representation of order higher than 0. The method includes: forming, based on the channels and for a current frame, a matrix of inter-channel covariance, and searching for eigenvectors of the covariance matrix with a view to obtaining a matrix of eigenvectors; testing the matrix of eigenvectors to verify that it represents a rotation in an N-dimensional space, and if not, correcting the matrix of eigenvectors until a rotation matrix is obtained, for the current frame; and applying the rotation matrix to the signals of the N channels before separate-channel encoding of the signals.
    Type: Grant
    Filed: February 10, 2020
    Date of Patent: March 5, 2024
    Assignee: ORANGE
    Inventors: Stéphane Ragot, Pierre Mahe
  • Publication number: 20240020949
    Abstract: A method for classifying at least one input image representing a target particle in a sample, involves implementing, by data processing of a client, steps of: (b) extracting the characteristic map of the target particle by a convolutional neural network pre-trained on a base of public images; (c) classifying the input image according to the extracted characteristic map.
    Type: Application
    Filed: October 19, 2021
    Publication date: January 18, 2024
    Applicants: BIOMERIEUX, BIOASTER
    Inventors: Pierre MAHÉ, Meriem EL AZAMI, Elodie DEGOUT-CHARMETTE, Zohreh SEDAGHAT, Quentin JOSSO, Fabian ROL
  • Publication number: 20230386176
    Abstract: A method for classifying at least one input image representing a target particle in a sample involves implementing, by data processing a client, steps of: (B) extracting a characteristic map of the target particle from the input image; (c) reducing the number of variables in the extracted characteristic map, using the t-SNE algorithm; (d) classifying, unsupervised, the input image based on the characteristic map having a reduced number of variables.
    Type: Application
    Filed: October 19, 2021
    Publication date: November 30, 2023
    Applicants: BIOASTER, BIOMERIEUX
    Inventors: Pierre MAHÉ, Meriem EL AZAMI, Elodie DEGOUT-CHARMETTE, Zohreh SEDAGHAT, Quentin JOSSO, Fabian ROL
  • Publication number: 20230386233
    Abstract: A method for classifying a sequence of input images representing a target particle in a sample over time, includes the following steps performed by the data processing of a client, namely: (b) concatenation of the input images in the sequence as a three-dimensional stack; (c) direct classification of the three-dimensional stack using a convolutional neural network, CNN
    Type: Application
    Filed: October 19, 2021
    Publication date: November 30, 2023
    Applicants: BIOMERIEUX, BIOASTER
    Inventors: Pierre MAHÉ, Meriem EL AZAMI, Elodie DEGOUT-CHARMETTE, Zohreh SEDAGHAT, Quentin JOSSO, Fabian ROL
  • Publication number: 20230386232
    Abstract: A method for classifying at least one input image containing a target particle in a sample, involves implementing, via data-processing of a client, steps of: (b) extracting a vector of characteristics of the target particle, the characteristics being numerical coefficients each associated with one elementary image of a set of elementary images each representing a reference particle, such that a linear combination of the elementary images weighted by the coefficients approximates the representation of the target particle in the input image; (c) classifying the input image depending on the extracted vector of characteristics.
    Type: Application
    Filed: October 19, 2021
    Publication date: November 30, 2023
    Applicants: BIOMERIEUX, BIOASTER
    Inventors: Pierre MAHÉ, Meriem EL AZAMI, Elodie DEGOUT-CHARMETTE, Zohreh SEDAGHAT, Quentin JOSSO, Fabian ROL
  • Patent number: 11749381
    Abstract: A method for identifying a pathogen contained in a metagenomic sample and for identifying pathogenic markers in the genome of the pathogen includes: processing the sample to extract DNA from pathogens, sequencing the extracted DNA, thereby producing a set of reads, comparing the reads to a database of genomes of known pathogens to assign reads to the pathogens; producing a pool of reads and assembling them to produce contigs, comparing the contigs to a second database of markers to check whether they contain a marker. The method further includes the step of comparing the reads to the second database to assign reads to the markers, a read being assigned to a marker if it falls entirely into or is astride the marker, and the pool also includes the reads assigned to the markers, the contigs thereby being assembled from reads assigned to a pathogen and reads assigned to markers.
    Type: Grant
    Filed: October 12, 2017
    Date of Patent: September 5, 2023
    Assignee: BIOMÉRIEUX
    Inventors: Pierre Mahe, Maud Tournoud, Stéphane Schicklin, Ghislaine Guigon, Etienne Ruppe
  • Patent number: 11649476
    Abstract: A method for quantifying the sensibility of a test microorganism to a concentration of an antimicrobial agent includes: preparing two liquid samples including the microorganism, one having the antimicrobial agent and one without; for each sample acquiring, by a flow cytometer, a digital set values including a fluorescence, forward, or side scatter distribution, and computing: a first coordinate value corresponding to the acquired distribution main mode and an acquired distribution first area for values greater than the first coordinate value, and a second coordinate value, greater than the first, for which an acquired distribution second area between the values equals a first area predefined percentage over 50%; computing a ratio according to: Q = QT ? ( ATB ) - Mode ? ( ATB ) QT ? ( no ? ? ATB ) - Mode ? ( no ? ? ATB ) where Mode(ATB) and QT(ATB) are the first and second coordinate values with the antimicrobial agent concentration, and Mode(no ATB) and QT(no ATB) are r
    Type: Grant
    Filed: July 6, 2017
    Date of Patent: May 16, 2023
    Assignee: BIOMÉRIEUX
    Inventors: Mahendrasingh Ramjeet, Pierre Mahe, Gaël Kaneko, Margaux Chapel
  • Publication number: 20230141128
    Abstract: A process of determining a phenotypic trait of a bacterial strain comprises sequencing part or all of the genome of the strain, and applying to the sequenced genome a predetermined model for predicting the trait, the model having groups of genome sequences as variables. According to the invention, the groups are chosen so that a co-occurrence rate in the genome of the bacterial species of the constituent genome sequences of the groups is above a predetermined threshold, and the groups are clusterings of the genome sequences according to their co-occurrence rates in the genome of the bacterial species.
    Type: Application
    Filed: March 10, 2021
    Publication date: May 11, 2023
    Applicant: BIOMÉRIEUX
    Inventors: Magali JAILLARD DANCETTE, Pierre MAHE
  • Publication number: 20230135480
    Abstract: A computer-implemented method for detecting a genome sequence in digital form in a genome of a microorganism in digital form, including:—storing, in a computer memory, a set of digital genome sequences of constant length k, or ‘k-mers’, the set being obtained by sliding, at a constant pitch, a window of length k over the genome sequence;—for each k-mer, determining its absence or presence in the genome;—determining that the genome sequence is present in the genome if the percentage of k-mers detected as present in the genome is higher than a predetermined threshold.
    Type: Application
    Filed: March 10, 2021
    Publication date: May 4, 2023
    Applicant: BIOMÉRIEUX
    Inventors: Philippine BARLAS, Magali JAILLARD DANCETTE, Meriem EL AZAMI, Pierre MAHE, Maud TOURNOUD, Pierre BERRIET
  • Patent number: 11414692
    Abstract: A method for determining a quantity Ginhib quantifying the inhibitory capacity of a molecule on a type of microorganism includes: preparing a plurality of samples, including microorganisms of the type, a nutrient medium for the microorganism and an initial amount of the molecule per microorganism increasing in a range [Qmin,Qmax] as a function of a classification of the samples; measuring the growth of the microorganisms in the samples as a function of time; and determining the quantity Ginhib as a function of the measurements of the growth. Determination of the quantity Ginhib includes: for each sample, calculating a value reflecting the growth of the microorganism of said type based on measurements of growth; classifying the values calculated for the samples as a function of the classification of the samples; and determining the quantity Ginhib as a function of the variation of the classified values.
    Type: Grant
    Filed: November 30, 2015
    Date of Patent: August 16, 2022
    Assignee: BIOMERIEUX
    Inventors: Maud Tournoud, Pierre Mahe
  • Patent number: 11408819
    Abstract: A detection of the Gram type of a bacterial strain includes: illumination, in the wavelength range 415 nm-440 nm, of at least one bacterium of said strain having a natural electromagnetic response in said range; acquisition, in the range 415 nm-440 nm, of a light intensity reflected by, or transmitted through, said illuminated bacterium; and determination of the Gram type of the bacterial strain as a function of the light intensity acquired in the range 415 nm-440 nm.
    Type: Grant
    Filed: June 13, 2017
    Date of Patent: August 9, 2022
    Assignee: BIOMÉRIEUX
    Inventors: Denis Leroux, Eric Laloum, Pierre Mahe, Rony Midahuen, Philippine Barlas
  • Publication number: 20220148607
    Abstract: A method and device for compressing audio signals forming, over time, a succession of sample frames, in each of N channels of an ambisonic representation of order higher than 0. The method includes: forming, based on the channels and for a current frame, a matrix of inter-channel covariance, and searching for eigenvectors of the covariance matrix with a view to obtaining a matrix of eigenvectors; testing the matrix of eigenvectors to verify that it represents a rotation in an N-dimensional space, and if not, correcting the matrix of eigenvectors until a rotation matrix is obtained, for the current frame; and applying the rotation matrix to the signals of the N channels before separate-channel encoding of the signals.
    Type: Application
    Filed: February 10, 2020
    Publication date: May 12, 2022
    Inventors: Stéphane Ragot, Pierre Mahe
  • Publication number: 20200118805
    Abstract: An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation f ? ( m ) = pN ? ( m | ? , ? ) pN ? ( m | ? , ? ) + ( 1 - p ) ? N ? ( m | ? _ , ? _ ) where: m is the distance calculated for the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range fr
    Type: Application
    Filed: December 9, 2019
    Publication date: April 16, 2020
    Applicant: BIOMERIEUX, INC.
    Inventors: Grégory Strubel, Maud Arsac, Denis Desseree, Pierre-Jean Cotte-Pattat, Pierre Mahe
  • Patent number: 10546735
    Abstract: An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation f ? ( m ) = pN ? ( m ? ? , ? ) pN ? ( m ? ? , ? ) + ( 1 - p ) ? N ? ( m ? ? _ , ? _ ) where: m is the distance calculated for the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|?,?) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range fr
    Type: Grant
    Filed: November 30, 2012
    Date of Patent: January 28, 2020
    Assignee: BIOMERIEUX, INC.
    Inventors: Grégory Strubel, Maud Arsac, Denis Desseree, Pierre-Jean Cotte-Pattat, Pierre Mahe
  • Publication number: 20190355440
    Abstract: A method for predicting the sensibility phenotype of a test microorganism to an antimicrobial agent amongst susceptible, intermediate and resistant phenotypes, including a learning stage and a prediction stage. The learning stage includes selecting a wide set of different strains having different known sensibility phenotypes determined according EUCAST or CLSI method, acquiring FCM distributions for each of the strain alicoted in liquid samples with fluorescent markers and different concentrations of the antibiotic, and performing a learning machine computing on mono or multidimensional spaces derived from the FCM acquisition to derive a prediction model of the sensibility phenotype to the antibiotic.
    Type: Application
    Filed: July 6, 2017
    Publication date: November 21, 2019
    Applicant: BIOMÉRIEUX
    Inventors: Mahendrasingh RAMJEET, Pierre MAHE, Gaël KANEKO, Margaux CHAPEL
  • Publication number: 20190352693
    Abstract: A method for quantifying the sensibility of a test microorganism to a concentration of an antimicrobial agent includes: preparing two liquid samples including the microorganism, one having the antimicrobial agent and one without; for each sample acquiring, by a flow cytometer, a digital set values including a fluorescence, forward, or side scatter distribution, and computing: a first coordinate value corresponding to the acquired distribution main mode and an acquired distribution first area for values greater than the first coordinate value, and a second coordinate value, greater than the first, for which an acquired distribution second area between the values equals a first area predefined percentage over 50%; computing a ratio according to: Q = QT ? ( ATB ) - Mode ? ( ATB ) QT ? ( no ? ? ATB ) - Mode ? ( no ? ? ATB ) where Mode(ATB) and QT(ATB) are the first and second coordinate values with the antimicrobial agent concentration, and Mode(no ATB) and QT(no ATB) are r
    Type: Application
    Filed: July 6, 2017
    Publication date: November 21, 2019
    Applicant: BIOMÉRIEUX
    Inventors: Mahendrasingh RAMJEET, Pierre MAHE, Gaël KANEKO, Margaux CHAPEL
  • Publication number: 20190323948
    Abstract: A detection of the Gram type of a bacterial strain includes: illumination, in the wavelength range 415 nm-440 nm, of at least one bacterium of said strain having a natural electromagnetic response in said range; acquisition, in the range 415 nm-440 nm, of a light intensity reflected by, or transmitted through, said illuminated bacterium; and determination of the Gram type of the bacterial strain as a function of the light intensity acquired in the range 415 nm-440 nm.
    Type: Application
    Filed: June 13, 2017
    Publication date: October 24, 2019
    Applicant: bioMérieux
    Inventors: Denis LEROUX, Eric LALOUM, Pierre MAHE, Rony MIDAHUEN, Philippine BARLAS
  • Publication number: 20190267226
    Abstract: A method of identifying by spectrometry unknown microorganisms from among a set of reference species, including a first step of supervised learning of a classification model of the reference species, a second step of predicting an unknown microorganism to be identified, including acquiring a spectrum of the unknown microorganism; and inferring from said spectrum and to the classification model at least one type of microorganism to which the unknown microorganism belong. The classification model is calculated by means of a structured multi-class SVM algorithm applied to the nodes of a tree-like hierarchical representation of the reference species in terms of evolution and/or of clinical phenotype and having margin constraints including so-called “loss” functions quantifying a proximity between the tree nodes.
    Type: Application
    Filed: May 9, 2019
    Publication date: August 29, 2019
    Applicant: bioMerieux
    Inventors: Kevin Vervier, Pierre Mahé, Jean-Baptsite Veyrieras
  • Publication number: 20190252042
    Abstract: A method for identifying a pathogen contained in a metagenomic sample and for identifying pathogenic markers in the genome of the pathogen includes: processing the sample to extract DNA from pathogens, sequencing the extracted DNA, thereby producing a set of reads, comparing the reads to a database of genomes of known pathogens to assign reads to the pathogens; producing a pool of reads and assembling them to produce contigs, comparing the contigs to a second database of markers to check whether they contain a marker. The method further includes the step of comparing the reads to the second database to assign reads to the markers, a read being assigned to a marker if it falls entirely into or is astride the marker, and the pool also includes the reads assigned to the markers, the contigs thereby being assembled from reads assigned to a pathogen and reads assigned to markers.
    Type: Application
    Filed: October 12, 2017
    Publication date: August 15, 2019
    Applicant: BIOMÉRIEUX
    Inventors: Pierre MAHE, Maud TOURNOUD, Stéphane SCHICKLIN, Ghislaine GUIGON, Etienne RUPPE