Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

J Mourao-Miranda; A Reinders; V Rocha-Rego; J Lappin; J Rondina; C Morgan; K D Morgan; P Fearon; P B Jones; G A Doody; R M Murray; S Kapur; P Dazzan

doi:10.1017/S0033291711002005

Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

J Mourao-Miranda, A Reinders, V Rocha-Rego, J Lappin, J Rondina, C Morgan, K D Morgan, P Fearon, P B Jones, G A Doody, R M Murray, S Kapur, P Dazzan

Research output: Contribution to journal › Article › peer-review

111 Citations (Scopus)

Abstract

To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

Original language	English
Pages (from-to)	1037-47
Number of pages	11
Journal	Psychological Medicine
Volume	42
Issue number	5
DOIs	https://doi.org/10.1017/S0033291711002005
Publication status	Published - May 2012

Keywords

Adult
Brain
Brain Mapping
Cohort Studies
Disease Progression
Female
Follow-Up Studies
Humans
Image Processing, Computer-Assisted
Individuality
Magnetic Resonance Imaging
Male
Observer Variation
Predictive Value of Tests
Psychotic Disorders
Reproducibility of Results
Support Vector Machines

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10.1017/S0033291711002005

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Mourao-Miranda, J., Reinders, A., Rocha-Rego, V., Lappin, J., Rondina, J., Morgan, C., Morgan, K. D., Fearon, P., Jones, P. B., Doody, G. A., Murray, R. M., Kapur, S., & Dazzan, P. (2012). Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. Psychological Medicine, 42(5), 1037-47. https://doi.org/10.1017/S0033291711002005

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abstract = "To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.",

keywords = "Adult, Brain, Brain Mapping, Cohort Studies, Disease Progression, Female, Follow-Up Studies, Humans, Image Processing, Computer-Assisted, Individuality, Magnetic Resonance Imaging, Male, Observer Variation, Predictive Value of Tests, Psychotic Disorders, Reproducibility of Results, Support Vector Machines",

author = "J Mourao-Miranda and A Reinders and V Rocha-Rego and J Lappin and J Rondina and C Morgan and Morgan, {K D} and P Fearon and Jones, {P B} and Doody, {G A} and Murray, {R M} and S Kapur and P Dazzan",

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doi = "10.1017/S0033291711002005",

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Mourao-Miranda, J , Reinders, A, Rocha-Rego, V, Lappin, J , Rondina, J , Morgan, C , Morgan, KD , Fearon, P, Jones, PB, Doody, GA, Murray, RM , Kapur, S & Dazzan, P 2012, 'Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study', Psychological Medicine, vol. 42, no. 5, pp. 1037-47. https://doi.org/10.1017/S0033291711002005

TY - JOUR

T1 - Individualized prediction of illness course at the first psychotic episode

T2 - a support vector machine MRI study

AU - Mourao-Miranda, J

AU - Reinders, A

AU - Rocha-Rego, V

AU - Lappin, J

AU - Rondina, J

AU - Morgan, C

AU - Morgan, K D

AU - Fearon, P

AU - Jones, P B

AU - Doody, G A

AU - Murray, R M

AU - Kapur, S

AU - Dazzan, P

PY - 2012/5

Y1 - 2012/5

N2 - To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

AB - To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.

KW - Adult

KW - Brain

KW - Brain Mapping

KW - Cohort Studies

KW - Disease Progression

KW - Female

KW - Follow-Up Studies

KW - Humans

KW - Image Processing, Computer-Assisted

KW - Individuality

KW - Magnetic Resonance Imaging

KW - Male

KW - Observer Variation

KW - Predictive Value of Tests

KW - Psychotic Disorders

KW - Reproducibility of Results

KW - Support Vector Machines

U2 - 10.1017/S0033291711002005

DO - 10.1017/S0033291711002005

M3 - Article

C2 - 22059690

SN - 0033-2917

VL - 42

SP - 1037

EP - 1047

JO - Psychological Medicine

JF - Psychological Medicine

IS - 5

ER -

Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

Abstract

Keywords

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