psychiatric classificationshow

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PSYCHO-INFORMATICS APPROACH IN PSYCHO-INFORMATICS APPROACH IN PSYCHIATRIC CLASSIFICATIONS PSYCHIATRIC CLASSIFICATIONS Debdulal Dutta Roy, Ph.D. Psychology Research Unit INDIAN STATISTICAL INSTITUTE, KOLKATA National Workshop on “ Psycho-informatics : Model for Measuring Randomized Psychological and Educational Data” 11-12 th March, 2013 Web: www.isical.ac.in/~ddroy

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Page 1: Psychiatric classificationshow

PSYCHO-INFORMATICS APPROACH PSYCHO-INFORMATICS APPROACH IN PSYCHIATRIC CLASSIFICATIONS IN PSYCHIATRIC CLASSIFICATIONS

Debdulal Dutta Roy, Ph.D.Psychology Research Unit

INDIAN STATISTICAL INSTITUTE, KOLKATANational Workshop on “ Psycho-informatics : Model for Measuring Randomized Psychological and Educational

Data”11-12th March, 2013

Web: www.isical.ac.in/~ddroy

Page 2: Psychiatric classificationshow

BACKGROUNDBACKGROUND

China, Japan and Latin American countries have own Psychiatric diagnostic classification systems.Does India need own ?Do the Indian Psychiatrists find difficulty to make distinct classifications ?What complaints are used by Indian Psychiatrists for classifications of psychiatric disorders ?

Page 3: Psychiatric classificationshow

DATA WAREHOUSE DATA WAREHOUSE

Previous psychiatric case history records of the department of psychiatry of one post graduate hospital. Here data are random, non-hypothesized and least structured.

Page 4: Psychiatric classificationshow

DATA RETRIEVING DATA RETRIEVING

Individual case wise all complaints and diagnostic classifications are retrieved.There were 20 complaints and 18 classifications

Page 5: Psychiatric classificationshow

DATA MINING DATA MINING

All the complaints were coded with 1,0 and Burt table was constructed.Burt table data were used in Correspondence analysis.

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Correspondence analysis provides correspondence mapCorrespondence map reveals extent of similarities and dissimilarities among the complaints, diagnostic classifications and between the two.

PATTERN RECOGNITION :PATTERN RECOGNITION :

Page 7: Psychiatric classificationshow

C orrespondence m ap o f psychia tric c lassifica tion and com pla intsInput Tab le (Rows x C o lum ns): 54 x 54 (B urt Table )

D imension 1 ; E igenva lue : .22772 (22 .77% o f Inertia ) Dim

ensi

on 2

; Eig

enva

lue:

.114

54 (1

1.45

% o

f Ine

rtia)

A NXC LS :0

A NXCLS :1

S O M A TCLS :0

S O M A TCLS :1

CO N V CLS :0

CO N V CLS :1

NE UDE P CL:0

NE UDE P CL:1

O CD CLS :0

O CDCLS :1

HY CH O CLS :0

HY CHO CLS :1

P H O B CLS :0

P HO B CLS :1

S CHIZC LS :0

S CHIZCLS :1M A NICCLS :0

M A NICCLS :1

P S Y D E P CL:0

P S Y D E P C L:1

P DDC LS :0

P DDC LS :1

S TRE CLS :0

S TRE CLS :1

S O M A TCO M :0S O M A TCO M :1

A NXCM P :0

A NXCM P :1

E M W DLCM P :0

E M W DLCM P :1

CO N DO CM P :0

CO N DO CM P :1

G UILTCM P :0

G UILTCM P :1

TE NS CM P :0

TE NS CM P :1

M A NCM P :0

M A NCM P :1

G RA NDCM P :0

G RA NDCM P :1DE P M DCM P :0

DE P M DC M P :1

HO S TCM P :0HO S TCM P :1 S US P ICM P :0

S U S P ICM P :1

HA LLUCM P :0

HA LLU CM P :1

UNTH CCM P :0UNTHCC M P :1

B LUA F CM P :0

B LUA F CM P :1

E XCITCM P :0E XCITCM P :1

-2 .0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

-2.0 -1.5 -1.0 -0.5 0.0 0 .5 1.0 1 .5

CORRESPONDENCE MAPCORRESPONDENCE MAP

Page 8: Psychiatric classificationshow

DISCOVERY OF KNOWLEDGEDISCOVERY OF KNOWLEDGE

Psychiatrists find difficulty to classify some symptoms distinctly.

This suggests need for creating Indian system of psychiatric classifications.

Psychiatric classifications should cover symptom dynamics and the etiology.

Page 9: Psychiatric classificationshow

Acknowledgment

Dr. Uday Sankar Mandal of IPGMR. I was co-guide of his MD dissertation titled “Mapping of Psychiatric Symptoms Across Different Demographic Groups: An Epidemiological problem” in 2008-2011.

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Thank youThank you