| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A hybrid approach to automatic de-identification of psychiatric notes
|
Lee, Hee-Jin
|
|
|
75 |
S |
p. S19-S27
|
artikel
|
| 2 |
A natural language processing challenge for clinical records: Research Domains Criteria (RDoC) for psychiatry
|
Uzuner, Özlem
|
|
|
75 |
S |
p. S1-S3
|
artikel
|
| 3 |
Automatic classification of RDoC positive valence severity with a neural network
|
Clark, Cheryl
|
|
|
75 |
S |
p. S120-S128
|
artikel
|
| 4 |
Automatic recognition of symptom severity from psychiatric evaluation records
|
Goodwin, Travis R.
|
|
|
75 |
S |
p. S71-S84
|
artikel
|
| 5 |
Counting trees in Random Forests: Predicting symptom severity in psychiatric intake reports
|
Scheurwegs, Elyne
|
|
|
75 |
S |
p. S112-S119
|
artikel
|
| 6 |
Cover 2: Editorial Board
|
|
|
|
75 |
S |
p. IFC
|
artikel
|
| 7 |
Cover 1/Spine
|
|
|
|
75 |
S |
p. OFC
|
artikel
|
| 8 |
De-identification of clinical notes via recurrent neural network and conditional random field
|
Liu, Zengjian
|
|
|
75 |
S |
p. S34-S42
|
artikel
|
| 9 |
De-identification of medical records using conditional random fields and long short-term memory networks
|
Jiang, Zhipeng
|
|
|
75 |
S |
p. S43-S53
|
artikel
|
| 10 |
De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1
|
Stubbs, Amber
|
|
|
75 |
S |
p. S4-S18
|
artikel
|
| 11 |
Exploring associations of clinical and social parameters with violent behaviors among psychiatric patients
|
Dai, Hong-Jie
|
|
|
75 |
S |
p. S149-S159
|
artikel
|
| 12 |
fmi-ii: Table of Contents
|
|
|
|
75 |
S |
p. i-ii
|
artikel
|
| 13 |
Learning to identify Protected Health Information by integrating knowledge- and data-driven algorithms: A case study on psychiatric evaluation notes
|
Dehghan, Azad
|
|
|
75 |
S |
p. S28-S33
|
artikel
|
| 14 |
Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores
|
Rios, Anthony
|
|
|
75 |
S |
p. S85-S93
|
artikel
|
| 15 |
Predicting mental conditions based on “history of present illness” in psychiatric notes with deep neural networks
|
Tran, Tung
|
|
|
75 |
S |
p. S138-S148
|
artikel
|
| 16 |
Predictive modeling for classification of positive valence system symptom severity from initial psychiatric evaluation records
|
Posada, Jose D.
|
|
|
75 |
S |
p. S94-S104
|
artikel
|
| 17 |
Psychiatric symptom recognition without labeled data using distributional representations of phrases and on-line knowledge
|
Zhang, Yaoyun
|
|
|
75 |
S |
p. S129-S137
|
artikel
|
| 18 |
Symptom severity classification with gradient tree boosting
|
Liu, Yang
|
|
|
75 |
S |
p. S105-S111
|
artikel
|
| 19 |
Symptom severity prediction from neuropsychiatric clinical records: Overview of 2016 CEGS N-GRID shared tasks Track 2
|
Filannino, Michele
|
|
|
75 |
S |
p. S62-S70
|
artikel
|
| 20 |
The UAB Informatics Institute and 2016 CEGS N-GRID de-identification shared task challenge
|
Bui, Duy Duc An
|
|
|
75 |
S |
p. S54-S61
|
artikel
|
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