Patents by Inventor Pablo Christian GERSBERG
Pablo Christian GERSBERG 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).
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Publication number: 20230343461Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: ApplicationFiled: June 14, 2023Publication date: October 26, 2023Inventors: Monika Sharma MELLEM, Yuelu Liu, Parvez Ahammad, Humberto Andres Gonzalez Cabezas, William J. Martin, Pablo Christian Gersberg
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Publication number: 20230343463Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions is selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: ApplicationFiled: May 2, 2023Publication date: October 26, 2023Inventors: Monika Sharma MELLEM, Yuelu LIU, Parvez AHAMMAD, Humberto Andres GONZALEZ CABEZAS, William J. MARTIN, Pablo Christian GERSBERG
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Patent number: 11715564Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: GrantFiled: May 1, 2019Date of Patent: August 1, 2023Assignee: NEUMORA THERAPEUTICS, INC.Inventors: Monika Sharma Mellem, Yuelu Liu, Parvez Ahammad, Humberto Andres Gonzalez Cabezas, William J. Martin, Pablo Christian Gersberg
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Patent number: 11676732Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions is selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: GrantFiled: September 1, 2021Date of Patent: June 13, 2023Assignee: NEUMORA THERAPEUTICS, INC.Inventors: Monika Sharma Mellem, Yuelu Liu, Parvez Ahammad, Humberto Andres Gonzalez Cabezas, William J. Martin, Pablo Christian Gersberg
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Publication number: 20210398685Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions is selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: ApplicationFiled: September 1, 2021Publication date: December 23, 2021Inventors: Monika Sharma MELLEM, Yuelu LIU, Parvez AHAMMAD, Humberto Andres GONZALEZ CABEZAS, William J. MARTIN, Pablo Christian GERSBERG
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Patent number: 11139083Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: GrantFiled: July 17, 2019Date of Patent: October 5, 2021Assignee: BlackThorn Therapeutics, Inc.Inventors: Monika Sharma Mellem, Yuelu Liu, Parvez Ahammad, Humberto Andres Gonzalez Cabezas, William J. Martin, Pablo Christian Gersberg
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Publication number: 20190355474Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: ApplicationFiled: July 17, 2019Publication date: November 21, 2019Applicant: BlackThorn Therapeutics, Inc.Inventors: Monika Sharma MELLEM, Yuelu LIU, Parvez AHAMMAD, Humberto Andres GONZALEZ CABEZAS, William J. MARTIN, Pablo Christian GERSBERG
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Publication number: 20190341152Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.Type: ApplicationFiled: May 1, 2019Publication date: November 7, 2019Inventors: Monika MELLEM, Yuelu LIU, Parvez AHAMMAD, Humberto GONZALEZ CABEZAS, William MARTIN, Pablo Christian GERSBERG