Description | n (%) | References |
---|---|---|
Main objective | ||
Information extraction | 45 (58%) | [29, 32,33,34,35,36, 38, 40,41,42,43,44,45, 49, 51, 58,59,60, 63,64,65,66, 68,69,70, 72, 73, 75, 76, 78,79,80, 82, 84,85,86,87, 89, 90, 94, 95, 100, 101, 103, 104] |
Information enrichment | 9 (12%) | |
Classification | 8 (10%) | |
Software development and evaluation | 6 (7.8%) | |
Prediction | 4 (5.2%) | |
Information comparison | 2 (2.6%) | |
Computer-assisted coding | 2 (2.6%) | |
Text processing | 1 (1.3%) | [74] |
Part of challenge | ||
i2b2 (Informatics for Integrating Biology and the Bedside) | 10 (13%) | |
Entire system | 8 (10%) | |
Parts of the system | 2 (2.6%) | |
SemEval (Semantic Evaluation) | 2 (2.6%) | |
Entire system | 1 (1.3%) | [41] |
Parts of the system | 1 (1.3%) | [83] |
ShARe/CLEF (Shared Annotated Resources/Conference and Labs of the Evaluation Forum) | 1 (1.3%) | [83] |
Parts of the system | 1 (1.3%) | [83] |
Dataset: language | ||
English | 60 (78%) | [11, 12, 29, 30, 32, 35, 37,38,39, 41,42,43,44,45,46,47, 49, 53, 55, 56, 58, 60, 62,63,64,65,66,67,68,69,70,71,72,73, 75,76,77,78,79,80,81, 83,84,85,86, 89, 90, 92,93,94,95,96,97,98,99,100,101,102,103,104] |
Spanish | 5 (6.5%) | |
French | 3 (3.9%) | |
German | 3 (3.9%) | |
Italian | 2 (2.6%) | |
Portuguese | 2 (2.6%) | |
Dutch | 1 (1.3%) | [57] |
Japanese | 1 (1.3%) | [91] |
Korean | 1 (1.3%) | [59] |
Dataset: Origin | ||
Data present in institute | 55 (71%) | [12, 29, 31, 32, 34,35,36, 38,39,40, 42, 43, 45, 47, 48, 50,51,52,53, 56, 57, 59,60,61,62,63,64,65,66,67, 70, 71, 74, 77,78,79,80,81,82,83,84,85,86, 88, 89, 91,92,93,94, 96, 97, 99, 101,102,103] |
Existing dataset | 25 (33%) | [11, 30, 33, 35, 37, 41, 44, 46, 49, 55, 58, 64, 68, 69, 72, 73, 75, 76, 83, 87, 90, 95, 98, 100, 104] |
Included reference to dataset | 21 (27%) | [11, 30, 35, 37, 41, 44, 46, 49, 55, 58, 64, 72, 75, 76, 83, 87, 90, 95, 98, 100, 104] |
Training of algorithm | ||
Trained | 47 (61%) | [11, 12, 29, 31, 32, 34, 37, 39, 41, 42, 44, 45, 48,49,50,51,52,53, 55,56,57,58,59, 62, 63, 65, 66, 68, 69, 73, 74, 76, 78,79,80,81,82,83,84, 87, 88, 90, 95, 96, 98, 99, 104] |
Not listed | 3 (3.9%) | |
Development of algorithm | ||
Use of development set | 16 (21%) | [12, 29, 31, 34, 37, 49, 55, 60, 63, 69, 74, 80, 87, 90, 94, 95] |
Not listed | 4 (5.2%) | |
Used NLP system or algorithm | ||
New NLP system or algorithm | 29 (38%) | [31, 32, 37, 43, 45, 47,48,49,50,51,52, 55, 57, 59, 68, 73, 74, 80, 82, 83, 85, 88, 89, 91, 94, 95, 100,101,102] |
New NLP system or algorithm with existing components | 25 (33%) | [12, 29, 34, 39, 41, 42, 44, 46, 58, 60,61,62,63, 66, 67, 69, 71, 75, 76, 78, 84, 87, 90, 98, 99] |
Existing NLP system or algorithm | 23 (30%) | [11, 30, 33, 35, 36, 38, 40, 53, 56, 64, 65, 70, 72, 77, 79, 81, 86, 93, 96, 97, 103, 104] |
Use in practice | ||
Plans to implement / still under development and testing | 12 (16%) | |
Implemented in practice | 10 (13%) | |
Availability of code | ||
Published algorithm or source code | 15 (20%) | |
Pseudocode in manuscript | 3 (3.9%) | |
Planning to publish algorithm or source code | 1 (1.3%) | [32] |
Not applicable, used an existing system | 20 (26%) | [11, 30, 33, 35, 36, 38, 40, 53, 64, 65, 70, 72, 77, 79, 81, 86, 93, 96, 103, 104] |