An updated, computable MEDication-Indication resource for biomedical research
© 2021. The Author(s)..
The MEDication-Indication (MEDI) knowledgebase has been utilized in research with electronic health records (EHRs) since its publication in 2013. To account for new drugs and terminology updates, we rebuilt MEDI to overhaul the knowledgebase for modern EHRs. Indications for prescribable medications were extracted using natural language processing and ontology relationships from six publicly available resources: RxNorm, Side Effect Resource 4.1, Mayo Clinic, WebMD, MedlinePlus, and Wikipedia. We compared the estimated precision and recall between the previous MEDI (MEDI-1) and the updated version (MEDI-2) with manual review. MEDI-2 contains 3031 medications and 186,064 indications. The MEDI-2 high precision subset (HPS) includes indications found within RxNorm or at least three other resources. MEDI-2 and MEDI-2 HPS contain 13% more medications and over triple the indications compared to MEDI-1 and MEDI-1 HPS, respectively. Manual review showed MEDI-2 achieves the same precision (0.60) with better recall (0.89 vs. 0.79) compared to MEDI-1. Likewise, MEDI-2 HPS had the same precision (0.92) and improved recall (0.65 vs. 0.55) than MEDI-1 HPS. The combination of MEDI-1 and MEDI-2 achieved a recall of 0.95. In updating MEDI, we present a more comprehensive medication-indication knowledgebase that can continue to facilitate applications and research with EHRs.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2021 |
---|---|
Erschienen: |
2021 |
Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
---|---|
Enthalten in: |
Scientific reports - 11(2021), 1 vom: 23. Sept., Seite 18953 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Zheng, Neil S [VerfasserIn] |
---|
Links: |
---|
Themen: |
---|
Anmerkungen: |
Date Completed 24.12.2021 Date Revised 11.11.2022 published: Electronic Citation Status MEDLINE |
---|
doi: |
10.1038/s41598-021-98579-4 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM330984837 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | NLM330984837 | ||
003 | DE-627 | ||
005 | 20231226203617.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231225s2021 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1038/s41598-021-98579-4 |2 doi | |
028 | 5 | 2 | |a pubmed24n1103.xml |
035 | |a (DE-627)NLM330984837 | ||
035 | |a (NLM)34556781 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Zheng, Neil S |e verfasserin |4 aut | |
245 | 1 | 3 | |a An updated, computable MEDication-Indication resource for biomedical research |
264 | 1 | |c 2021 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 24.12.2021 | ||
500 | |a Date Revised 11.11.2022 | ||
500 | |a published: Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a © 2021. The Author(s). | ||
520 | |a The MEDication-Indication (MEDI) knowledgebase has been utilized in research with electronic health records (EHRs) since its publication in 2013. To account for new drugs and terminology updates, we rebuilt MEDI to overhaul the knowledgebase for modern EHRs. Indications for prescribable medications were extracted using natural language processing and ontology relationships from six publicly available resources: RxNorm, Side Effect Resource 4.1, Mayo Clinic, WebMD, MedlinePlus, and Wikipedia. We compared the estimated precision and recall between the previous MEDI (MEDI-1) and the updated version (MEDI-2) with manual review. MEDI-2 contains 3031 medications and 186,064 indications. The MEDI-2 high precision subset (HPS) includes indications found within RxNorm or at least three other resources. MEDI-2 and MEDI-2 HPS contain 13% more medications and over triple the indications compared to MEDI-1 and MEDI-1 HPS, respectively. Manual review showed MEDI-2 achieves the same precision (0.60) with better recall (0.89 vs. 0.79) compared to MEDI-1. Likewise, MEDI-2 HPS had the same precision (0.92) and improved recall (0.65 vs. 0.55) than MEDI-1 HPS. The combination of MEDI-1 and MEDI-2 achieved a recall of 0.95. In updating MEDI, we present a more comprehensive medication-indication knowledgebase that can continue to facilitate applications and research with EHRs | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, N.I.H., Extramural | |
700 | 1 | |a Kerchberger, V Eric |e verfasserin |4 aut | |
700 | 1 | |a Borza, Victor A |e verfasserin |4 aut | |
700 | 1 | |a Eken, H Nur |e verfasserin |4 aut | |
700 | 1 | |a Smith, Joshua C |e verfasserin |4 aut | |
700 | 1 | |a Wei, Wei-Qi |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Scientific reports |d 2011 |g 11(2021), 1 vom: 23. Sept., Seite 18953 |w (DE-627)NLM215703936 |x 2045-2322 |7 nnns |
773 | 1 | 8 | |g volume:11 |g year:2021 |g number:1 |g day:23 |g month:09 |g pages:18953 |
856 | 4 | 0 | |u http://dx.doi.org/10.1038/s41598-021-98579-4 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 11 |j 2021 |e 1 |b 23 |c 09 |h 18953 |