Machine learning and data mining: strategies for hypothesis generation. - Wikidata - wikimedia - TriplyDB

Machine learning and data mining: strategies for hypothesis generation.

Machine learning and data mining: strategies for hypothesis generation.

http://www.wikidata.org/entity/Q34122278

about

A proposal for assessing study quality: Biomonitoring, Environmental Epidemiology, and Short-lived Chemicals (BEES-C) instrument Transitioning to a Data Driven Mental Health Practice: Collaborative Expert Sessions for Knowledge and Hypothesis Finding Multiple kernel learning with random effects for predicting longitudinal outcomes and data integration.Data Mining Techniques Applied to Hydrogen Lactose Breath Test Inferring population structure and relationship using minimal independent evolutionary markers in Y-chromosome: a hybrid approach of recursive feature selection for hierarchical clustering Recent developments in multivariate pattern analysis for functional MRI.A pilot study investigating changes in neural processing after mindfulness training in elite athletes.The future of medical diagnostics: large digitized databases.Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives.Acute Mental Discomfort Associated with Suicide Behavior in a Clinical Sample of Patients with Affective Disorders: Ascertaining Critical Variables Using Artificial Intelligence Tools.The role of machine learning in neuroimaging for drug discovery and development.Predicting suicidal behavior: are we really that far along? Comment on "Discovery and validation of blood biomarkers for suicidality".Suicide detection in Chile: proposing a predictive model for suicide risk in a clinical sample of patients with mood disorders.A Cross-National Tool for Assessing and Studying Suicidal Behaviors.Detecting intentional insulin omission for weight loss in girls with type 1 diabetes mellitus.Unsupervised classification of major depression using functional connectivity MRI.Development of diagnostic model of lung cancer based on multiple tumor markers and data mining.Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan.From eHealth to iHealth: Transition to Participatory and Personalized Medicine in Mental Health.Individualized Prediction and Clinical Staging of Bipolar Disorders using Neuroanatomical Biomarkers

P2860

Q28386897-A960E291-E53B-4279-842D-74ABB9963F13 Q28596540-428CE66F-577F-4D48-8F95-CC3F61AF3117 Q30980714-30D7D736-0F91-4079-BE80-6EFAA4483A55 Q31157045-27680E71-38F0-4371-A469-103AD8A4A713 Q34115377-227C720D-2BD9-4804-84FC-C848CACB3544 Q34351914-4C0A29B0-2594-4F5B-9BA1-B72BA8337E7C Q35999176-F86EA871-7D7D-43E5-9C2F-1F3BC14A9EE1 Q36247947-14CB28B8-4498-4D56-A027-648DF1578D4A Q36388848-EA8E0769-082F-4F40-8B37-610E70EAAAE9 Q37621113-A39ED3C5-67F5-464E-9FD3-4CE40D3667C2 Q38503576-3803A12B-6764-488B-838D-4D15C15E17C2 Q38535676-57E94EE6-A8EE-41E1-8410-C56F09F0B69C Q39247470-FA532CCB-FC31-4E3F-8540-10E5EC717A8E Q41662363-C04B50AA-6F4B-4A3F-9EA3-A70D5FFC4E54 Q45959234-50F8D138-BA8B-44E5-B8B4-6D6A8A1A0C96 Q45959309-42661FA6-6E44-4E38-8ED6-D27D9BD73E19 Q47129139-A8D0610E-E910-4118-9900-DB4B11386804 Q47172206-4509DACF-B397-4CC1-8220-948DA102AD52 Q47213143-0A921DC4-0899-4029-A7BF-78A87659C00F Q57411097-49AA1369-38D7-43C4-B3AB-B08897E3CFDF

P2860

Machine learning and data mining: strategies for hypothesis generation.

http://www.wikidata.org/entity/Q34122278

description

2012 nî lūn-bûn

@nan

2012 թուականի Յունուարին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի հունվարին հրատարակված գիտական հոդված

@hy

2012年の論文

@ja

2012年論文

@yue

2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

@zh-tw

2012年论文

@wuu

name

Machine learning and data mining: strategies for hypothesis generation.

@ast

Machine learning and data mining: strategies for hypothesis generation.

@en

Machine learning and data mining: strategies for hypothesis generation.

@nl

type

label

Machine learning and data mining: strategies for hypothesis generation.

@ast

Machine learning and data mining: strategies for hypothesis generation.

@en

Machine learning and data mining: strategies for hypothesis generation.

@nl

prefLabel

Machine learning and data mining: strategies for hypothesis generation.

@ast

Machine learning and data mining: strategies for hypothesis generation.

@en

Machine learning and data mining: strategies for hypothesis generation.

@nl

P1433

Q34122278-C59BF24F-0B9C-4BF9-996E-894F23D901EA

P1476

Q34122278-699123F4-866D-448F-A342-ABF941C2A44C

P2093

Q34122278-13787E9F-7642-44D5-AB85-85407F6BE414

Q34122278-2FDA933A-5CD2-4B66-90B9-73B7BF5417F6

Q34122278-36DF7579-A471-4819-85F6-93B27EE35F34

Q34122278-81FAC461-E786-492A-B2DD-4460ED1F7459

Q34122278-83C5E859-8C74-4FEF-9086-56B8F81A229F

Q34122278-8EB18329-91D5-4A2F-9863-479AAAC8D5A2

Q34122278-E10E32D4-2E71-496B-933D-BF6912745AD1

P2860

Q34122278-356DFC64-0670-48E0-98B3-D5743A16AD75

Q34122278-3954AD22-88A3-4A76-A381-02102CBCE9C0

Q34122278-6EF42B2E-71C1-4833-B681-C63748058A42

Q34122278-97FF3850-3684-46E2-8722-BBE2BE76CDE8

Q34122278-AD5879DF-3930-4CC8-B6B5-444D01B2740A

Q34122278-BDDE88EF-C1A4-4DE2-AD2C-BB1317979662

Q34122278-D3992B35-670A-43E8-BC48-BC5491014CF4

Q34122278-D4814FEA-564B-4679-A596-B152900C8EDF

Q34122278-F5ACD2B5-A40A-4FE2-A61C-41CE3AD82D7B

P2888

Q34122278-A59C3A64-8DF6-456E-BE50-7D7E21D29F6D

P304

Q34122278-32A6209D-388B-4B9B-BCBE-7FE9770A7714

P31

Q34122278-D7D36B30-C5D5-4FB7-8379-C07B4713FD53

P356

Q34122278-B995ECBC-ED94-4E5A-BAA6-A6A3992A37EB

P407

Q34122278-F29FEC96-0AFC-4FAC-8E3B-5E701DB192FF

P433

Q34122278-46B02B96-F2F2-4480-A189-C19DF9CC5BD6

P478

Q34122278-11737970-A957-4073-97C4-C669919EDD4A

P50

Q34122278-776F3416-42E7-4C57-B259-0A1F9DC16038

P577

Q34122278-BE2C3E8A-128C-438B-A9ED-3E78C0CFDDBF

P5875

Q34122278-2CF8FB0A-0C22-4481-9DCB-02BAA6F5ECCE

P6179

Q34122278-88C3A676-FEC2-4346-914C-64B2D70BDC36

P698

Q34122278-4271B6DE-3736-481A-B8DF-73E6EBE64555

P921

Q34122278-6D824CD0-B113-4F7D-8D88-79AC13BB7493

P356

P1433

Molecular Psychiatry

P1476

Machine learning and data mining: strategies for hypothesis generation.

@en

P2093

A Artés-Rodríguez

http://www.w3.org/2001/XMLSchema#string

D Madigan

http://www.w3.org/2001/XMLSchema#string

F Perez-Cruz

http://www.w3.org/2001/XMLSchema#string

H Blasco-Fontecilla

http://www.w3.org/2001/XMLSchema#string

H C Galfalvy

http://www.w3.org/2001/XMLSchema#string

M A Oquendo

http://www.w3.org/2001/XMLSchema#string

N Duan

http://www.w3.org/2001/XMLSchema#string

P2860

Data mining: data analysis on a grand scale?

Elucidating a magnetic resonance imaging-based neuroanatomic biomarker for psychosis: classification analysis using probabilistic brain atlas and machine learning algorithms

A paradigm shift in brain research.

Harnessing experience: exploring the gap between evidence-based medicine and clinical practice.

Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins.

Selective serotonin reuptake inhibitors in pregnant women and neonatal withdrawal syndrome: a database analysis.

Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI.

An evaluation of three signal-detection algorithms using a highly inclusive reference event database.

Diagnostic stability and evolution of bipolar disorder in clinical practice: a prospective cohort study.

P2888

P304

956-959

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P356

10.1038/MP.2011.173

http://www.w3.org/2001/XMLSchema#string

P407

P433

10

http://www.w3.org/2001/XMLSchema#string

P478

17

http://www.w3.org/2001/XMLSchema#string

P50

Enrique Baca-Garcia

P577

2012-01-10T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

221734445

http://www.w3.org/2001/XMLSchema#string

P6179

1032143563

http://www.w3.org/2001/XMLSchema#string

P698

22230882

http://www.w3.org/2001/XMLSchema#string

P921

machine learning