SE2051358A1 - System for determining a representation of a subjective state of an individual, use thereof and a computer program product - Google Patents

System for determining a representation of a subjective state of an individual, use thereof and a computer program product

Info

Publication number
SE2051358A1
SE2051358A1 SE2051358A SE2051358A SE2051358A1 SE 2051358 A1 SE2051358 A1 SE 2051358A1 SE 2051358 A SE2051358 A SE 2051358A SE 2051358 A SE2051358 A SE 2051358A SE 2051358 A1 SE2051358 A1 SE 2051358A1
Authority
SE
Sweden
Prior art keywords
semantic
individual
function
question
subjective state
Prior art date
Application number
SE2051358A
Inventor
Katarina Kjell
Oscar Kjell
Sverker Sikström
Original Assignee
Worddiagnostics Ab
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Worddiagnostics Ab filed Critical Worddiagnostics Ab
Priority to SE2051358A priority Critical patent/SE2051358A1/en
Publication of SE2051358A1 publication Critical patent/SE2051358A1/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Epidemiology (AREA)
  • Biomedical Technology (AREA)
  • Primary Health Care (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The disclosure relates to a system for determining a representation of a subjective state of an individual, and to use thereof and a computer program product. The system executes:a transformation function providing a set of one or more semantic representation vectors each representing an answer to a semantic question, a first prediction function configured to combine one or more rating values, obtained from the individual answering a rating scale, with each semantic representation vector representing an answer to a semantic question and thereby provide a set of a plurality of first predictions concerning the subjective state of the individual, wherein there is provided a first prediction for each semantic representation vector representing an answer to a semantic question,a second prediction function configured to combine the first predictions into a combined second prediction concerning the subjective state of an individual.

Claims (13)

1. System for determining a representation of a subjective state of anindividual, the system comprising: a control circuit configured to execute: a transformation function configured to transform at least onedescriptive word or text obtained from the individual answering a semanticquestion into one semantic representation vector, thereby providing a set ofone or more semantic representation vectors each representing an answer toa semantic question, a first prediction function configured to combine one or more ratingvalues, obtained from the individual answering a rating scale, with eachsemantic representation vector representing an answer to a semanticquestion and thereby provide a set of a plurality of first predictions concerningthe subjective state of the individual, wherein there is provided a firstprediction for each semantic representation vector representing an answer toa semantic question, a second prediction function configured to combine the first predictionsinto a combined second prediction concerning the subjective state of an individual.
2. System according to claim 1, wherein the control circuit is configuredto, before the execution of the transformation function, execute:a semantic input function configured to receive at least one descriptive word or text obtained from the individual answering a semantic question.
3. System according to claim 2, wherein the transformation function isconfigured to transform at least one descriptive word or text obtained from theindividual answering a semantic question into one semantic representationvector, and wherein the individual is requested to answer a plurality of semantic questions such that the transformation function provides a set of a plurality of semantic representation vectors each representing an answer to a semantic question.
4. System according to c|aims 2 or 3, wherein the control circuit isfurther configured to, before the execution of the semantic input function,execute: a selection function configured to select from a database containing aplurality of semantic questions a semantic question to be presented to anindividual, and a presentation function configured to present the selected semantic question to the individual.
5. System according to any one of c|aims 1-4, wherein the controlcircuit is configured to, before the execution of the transformation function,execute: a rating input function configured to receive at least one rating value obtained from the individual answering one or more rating scales.
6. System according to any one of c|aims 1-5, wherein the firstprediction function is based on a learning process based on a plurality ofindividual's having a determined subjective state and answering one or more rating scales and one or more semantic questions.
7. System according to any one of c|aims 1-6, wherein the firstprediction function is based on a model having linear properties, such as multiple linear regression, multiple linear ridge regression.
8. System according to any one of c|aims 1-7, wherein the secondprediction concerning the subjective state of an individual represents adegree of fulfilment of one of more subjective states.
9. System according to any one of claims 1-8, wherein the secondprediction function is based on a model representing Iikelihoods, such as multiple linear logistic regressions, multiple logistic ridge regression.
10. System according to any one of claims 1-9, where the firstpredictions function is based on semantic similarity scales, semanticpredicted rating scales, semantic-numeric correlation, semantic predicted valence scales.
11. Use of a system according to any one of claims 1-10 to determinea subjective state of an individual, the subjective state preferably relating to orforming part of a diagnosis of a first mental illness or psychiatric disorder,such as anxiety and/or depression.
12. Use of a system according to any one of claims 1-10 to provide asecond prediction of a subjective state of an individual relating to a firstmental illness or psychiatric disorder and to provide a second prediction of asubjective state of an individual relating to a second mental illness orpsychiatric disorder, the system thereby being used to provide or form part of a diagnosisdistinguishing between the first and the second mental illnesses or psychiatric disorders.
13. Computer program product stored on a non-transitory computerreadable medium, which computer program product when executed on acomputer, controls the electronic circuitry of the computer to execute the functions of the system according to any one of claims 1-10.
SE2051358A 2020-11-20 2020-11-20 System for determining a representation of a subjective state of an individual, use thereof and a computer program product SE2051358A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
SE2051358A SE2051358A1 (en) 2020-11-20 2020-11-20 System for determining a representation of a subjective state of an individual, use thereof and a computer program product

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE2051358A SE2051358A1 (en) 2020-11-20 2020-11-20 System for determining a representation of a subjective state of an individual, use thereof and a computer program product

Publications (1)

Publication Number Publication Date
SE2051358A1 true SE2051358A1 (en) 2022-05-21

Family

ID=82020804

Family Applications (1)

Application Number Title Priority Date Filing Date
SE2051358A SE2051358A1 (en) 2020-11-20 2020-11-20 System for determining a representation of a subjective state of an individual, use thereof and a computer program product

Country Status (1)

Country Link
SE (1) SE2051358A1 (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20110127029A (en) * 2010-05-18 2011-11-24 경희대학교 산학협력단 Method for estimating degree of subjective well-being based on language of user
US20140309989A1 (en) * 2008-11-04 2014-10-16 Saplo Ab Method and system for analyzing text
WO2017015392A1 (en) * 2015-07-21 2017-01-26 The Arizona Obard Of Regents On Behalf Of The University Of Arizona Systems and methods for analyzing healthcare data
WO2019182508A1 (en) * 2018-03-23 2019-09-26 Kjell Oscar Method for determining a representation of a subjective state of an individual with vectorial semantic approach

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140309989A1 (en) * 2008-11-04 2014-10-16 Saplo Ab Method and system for analyzing text
KR20110127029A (en) * 2010-05-18 2011-11-24 경희대학교 산학협력단 Method for estimating degree of subjective well-being based on language of user
WO2017015392A1 (en) * 2015-07-21 2017-01-26 The Arizona Obard Of Regents On Behalf Of The University Of Arizona Systems and methods for analyzing healthcare data
WO2019182508A1 (en) * 2018-03-23 2019-09-26 Kjell Oscar Method for determining a representation of a subjective state of an individual with vectorial semantic approach

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Cohen et al., "Simulating expert Clinical comprehension: Adapting latent semantic analysis to accurate axtract Clinical concepts from pwychiatric narrative", Journal of Biomedical Informatics (2008), Vol. 41, Nr. 6, pages 1070-1097 *
Kjel et al. "The harmony in life scale complements the satisfaction with Life scale: expanding the conceptualization of the cognitive Component of subjective well-being", Social Indicators Research (2015), Vol. 126, Nr. 2, pages 908-914 *
Neuman et al., "A vectorial semantics Approach to personality assessment", Scientific Reports (2014), Vol. 4, Nr. 4761, pages 1-6 *

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