Patents by Inventor Mark Finlayson
Mark Finlayson 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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Patent number: 11537888Abstract: Devices and methods for learning and/or predicting the self-reported pain improvement levels of osteoarthritis (OA) patients are provided. A device or apparatus can include a processor and a machine-readable medium in operable communication with the processor and having stored thereon an algorithm and a unique set of features. The algorithm and set of features can enable building one or more models that learn the self-reported pain improvement levels of OA patients.Type: GrantFiled: May 15, 2020Date of Patent: December 27, 2022Assignee: THE FLORIDA INTERNATIONAL UNIVERSITY BOARD OF TRUSTEESInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Patent number: 11494418Abstract: Systems and methods for discovering and/or determining section types for a given document class in a data-driven manner are provided. A modified Bayesian model merging algorithm can be used, along with extending an Analogical Story Merging (ASM) algorithm. The systems and methods can learn the section structure of documents without a pre-existing ontology of sections or time-intensive annotation efforts.Type: GrantFiled: January 28, 2021Date of Patent: November 8, 2022Assignee: THE FLORIDA INTERNATIONAL UNIVERSITY BOARD OF TRUSTEESInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Publication number: 20220237210Abstract: Systems and methods for discovering and/or determining section types for a given document class in a data-driven manner are provided. A modified Bayesian model merging algorithm can be used, along with extending an Analogical Story Merging (ASM) algorithm. The systems and methods can learn the section structure of documents without a pre-existing ontology of sections or time-intensive annotation efforts.Type: ApplicationFiled: January 28, 2021Publication date: July 28, 2022Applicant: The Florida International University Board of TrusteesInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Patent number: 11170303Abstract: Systems and methods for quantifying temporal indeterminacy of timelines are provided. Systems and methods can rely on solving temporal constraint problems to extract timelines and can calculate the temporal relation loss during timeline transformation and then identify the temporal indeterminate sections of extracted timelines from both timelines and temporal graphs to measure the total temporal information loss.Type: GrantFiled: January 28, 2021Date of Patent: November 9, 2021Assignee: THE FLORIDA INTERNATIONAL UNIVERSITY BOARD OF TRUSTEESInventors: Mustafa Ocal, Mark Finlayson
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Patent number: 10949622Abstract: Systems and methods for automatically modeling the discourse structure of psychiatric reports and segmenting these reports into various sections are provided. The systems and methods can be based around a model that learns the section types, positions, and sequence and can automatically segment unlabeled text in a psychiatric report into the corresponding sections. Knowledge of the ordering of the sections can improve the performance of a section classifier and a text segmenter. A Hierarchical Hidden Markov Model (HHMM) can be trained and can categorize sections in psychiatric reports into a predefined section label.Type: GrantFiled: October 30, 2019Date of Patent: March 16, 2021Assignee: The Florida International University Board of TrusteesInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Patent number: 10909324Abstract: Methods and devices for story detection in text are provided. A device can include an input device for receiving text data a processor configured to: tokenize each paragraph in the text data and split each tokenized paragraph into sentences; parse each sentence from the tokenized paragraphs; label each predicate in each sentence with its respective semantic role; and assign a verb class to each predicate; and determine whether respective arguments of each predicate contains a character. The device can further include a support vector machine configured to determine whether a story is present within each paragraph based upon whether each predicate contains a character.Type: GrantFiled: January 29, 2019Date of Patent: February 2, 2021Assignee: The Florida International University Board of TrusteesInventors: Joshua Daniel Eisenberg, Mark Finlayson
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Publication number: 20200364566Abstract: Devices and methods for learning and/or predicting the self-reported pain improvement levels of osteoarthritis (OA) patients are provided. A device or apparatus can include a processor and a machine-readable medium in operable communication with the processor and having stored thereon an algorithm and a unique set of features. The algorithm and set of features can enable building one or more models that learn the self-reported pain improvement levels of OA patients.Type: ApplicationFiled: May 15, 2020Publication date: November 19, 2020Applicant: The Florida International University Board of TrusteesInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Publication number: 20200134024Abstract: Systems and methods for automatically modeling the discourse structure of psychiatric reports and segmenting these reports into various sections are provided. The systems and methods can be based around a model that learns the section types, positions, and sequence and can automatically segment unlabeled text in a psychiatric report into the corresponding sections. Knowledge of the ordering of the sections can improve the performance of a section classifier and a text segmenter. A Hierarchical Hidden Markov Model (HHMM) can be trained and can categorize sections in psychiatric reports into a predefined section label.Type: ApplicationFiled: October 30, 2019Publication date: April 30, 2020Applicant: The Florida International University Board of TrusteesInventors: Deya Banisakher, Naphtali Rishe, Mark Finlayson
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Publication number: 20200081980Abstract: Methods and devices for story detection in text are provided. A device can include an input device for receiving text data a processor configured to: tokenize each paragraph in the text data and split each tokenized paragraph into sentences; parse each sentence from the tokenized paragraphs; label each predicate in each sentence with its respective semantic role; and assign a verb class to each predicate; and determine whether respective arguments of each predicate contains a character. The device can further include a support vector machine configured to determine whether a story is present within each paragraph based upon whether each predicate contains a character.Type: ApplicationFiled: January 29, 2019Publication date: March 12, 2020Applicant: The Florida International University Board of TrusteesInventors: Joshua Daniel Eisenberg, Mark Finlayson
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Patent number: 10191975Abstract: Methods for classifying a point of view and diegesis are provided. A method can include providing a processor in operable communication with a computer-readable medium, receiving a narrative text, extracting a set of features from the narrative text, transmitting the features into a feature vector, transmitting a plurality of feature vectors to a support vector machine, predicting a point of view and diegesis for the narrative text associate with a particular feature vector, and annotating the narrative text.Type: GrantFiled: November 16, 2017Date of Patent: January 29, 2019Assignee: The Florida International University Board of TrusteesInventors: Joshua Daniel Eisenberg, Mark Finlayson