Children's Hospital Medical Center

University of Southern California

Cincinnati Children's Hospital Medical Center

John P Pestian

Tracy A Glauser

Robert A Kowatch

Pawel Matykiewicz

Jacqueline M Grupp-Phelan

Wlodzislaw Duch

Michael Sorter

Bruce Aronow

Richard J Wenstrup

Stefan Scherer

Louis-Philippe Morency

Alexander A Vinks

Richard Wenstrup

Shannon Michelle Standridge

Kevin Bretonnel Cohen

Hansel M Greiner

Katherine D Holland

A method for performing natural language processing of free text using domain-specific spreading activation. Embodiments of the present invention ontologize free text using an algorithm based on neurocognitive theory by simulating human recognition, semantic, and episodic memory approaches. Embodiments of the invention may be used to process clinical text for assignment of billing codes, analyze suicide notes or legal discovery materials, and for processing other collections of text. Further, embodiments of the invention may be used to more effectively search large databases, such as a database containing a large number of medical publications.

Processing text with domain-specific spreading activation methods

A method for assessing a neuropsychiatric condition (such as, but not limited to, a risk that a subject may attempt to commit suicide or repeat an attempt to commit suicide, a risk that terminally ill patient is not being care-for or treated according to the patient's true wishes, a risk that a subject may perform or repeat a criminal act and/or a harmful act, a risk of the subject having a psychiatric illness, and/or a risk of a subject feigning a psychiatric illness) may include a plurality of steps. A step may include receiving biomarker data associated from an analysis of the subject's biological sample and a step of receiving thought-marker data obtained pertaining to one or more of the subject's recorded thoughts, spoken words, transcribed speech, and writings. A step may include generating a biomarker score associated with the neuropsychiatric condition from the biomarker data. A step may include generating a thought-marker score associated with the neuropsychiatric condition from the thought-marker data. And a step may involve calculating a neuropsychiatric condition score based, at least in part, upon the biomarker score and the thought-marker score. Such method may be operating from one or more memory devices including computer-readable instructions configured to instruct a computerized system to perform the method, and the method may be operating on a computerized system including one or more computer servers (or other available devices) accessible over a computer network such as the Internet or over some other data network.

Computer implemented system and method for assessing a neuropsychiatric condition of a human subject

A method for assessing suicide risk for a human subject including receiving recorded voice data of the subject; and classifying the subject as suicidal or non-suicidal based upon a computerized analysis of one or more nonverbal characteristics of the speech data, especially features associated with a breathy phonation type. The analysis of the nonverbal characteristics of the voice data can include an analysis of acoustic characteristics of speech, and/or an analysis of prosodic and voice quality-related features of the voice data. Related apparatus, systems, techniques and articles are also described.

System and method for assessing suicide risk of a patient based upon non-verbal characteristics of voice data

The invention provides population models, methods, and algorithms for targeting a dosing regimen or compound selection to an individual patient. The methods and algorithms of the invention utilize population models that incorporate genotype information for genes encoding drug metabolizing enzymes for one or more compounds of interest. The methods allow integration of genotype information for one or more genes encoding a drug metabolizing enzyme, particularly a cytochrome P450 gene with patient data. The methods allow integration of genotype information and the effect of one or more compounds on one or more drug metabolizing enzymes. The methods allow iterative feedback of drug metabolizing data obtained from a patient into the process of generating a dosage regimen recommendation for a compound of interest for an individual patient.

Optimization and individualization of medication selection and dosing

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Loveland, OH, United States of America

John P Pestian