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JSON file with abstracts from Lilacs and Ibecs with ICD10 codes (ICD10-CM and ICD10-PCS) associated to them (CIE10 in Spanish). These databases have MeSH terms describing some of their documents. Then, using UMLS Metathesaurus, those MeSH terms have been translated into ICD10 codes (ICD10-CM and ICD10-PCS). Every abstract have at least one ICD10 code. In addition, MeSH codes given by the databases (Lilacs and Ibecs) have a "word" describing them. These "words" have been used to add further ICD10 codes. We have done strict string matching to find whether those "words" were a descriptor of any ICD10 code (in the Spanish version, CIE10). The format of the JSON file is the following: {'articles': [{'title': 'title', 'pmid': 'pmid', 'abstractText': 'abtract (in Spanish)', 'Mesh': [{'Code': 'MeSHCode', 'Word': 'reference', 'CIE': [CIE10_1, CIE10_2, ...]}, ...] }, ...] } Corpus statistics: There are 176 294 abstracts. On average, every abstract has 2,5 associated ICD10 codes. There are 3103 unique ICD10 codes (ICD10-CM and ICD10-PCS).
Funded by the Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 32 | |
| downloads | 6 |

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