Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge
In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Schäfer, Henning [verfasserIn] Idrissi-Yaghir, Ahmad [verfasserIn] Bewersdorff, Jeanette [verfasserIn] Frihat, Sameh [verfasserIn] Friedrich, Christoph M. [verfasserIn] Zesch, Torsten [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of biomedical informatics - San Diego, Calif. : Academic Press, 2001, 143 |
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| Übergeordnetes Werk: |
volume:143 |
| DOI / URN: |
10.1016/j.jbi.2023.104400 |
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| Katalog-ID: |
ELV060735686 |
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| 520 | |a In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. | ||
| 650 | 4 | |a Medication extraction | |
| 650 | 4 | |a Event classification | |
| 650 | 4 | |a Named entity recognition | |
| 650 | 4 | |a Transformer-architecture | |
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| 700 | 1 | |a Bewersdorff, Jeanette |e verfasserin |0 (orcid)0000-0002-9091-2892 |4 aut | |
| 700 | 1 | |a Frihat, Sameh |e verfasserin |4 aut | |
| 700 | 1 | |a Friedrich, Christoph M. |e verfasserin |0 (orcid)0000-0001-7906-0038 |4 aut | |
| 700 | 1 | |a Zesch, Torsten |e verfasserin |0 (orcid)0000-0002-9678-3825 |4 aut | |
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10.1016/j.jbi.2023.104400 doi (DE-627)ELV060735686 (ELSEVIER)S1532-0464(23)00121-1 DE-627 ger DE-627 rda eng 330 004 570 VZ 44.32 bkl Schäfer, Henning verfasserin (orcid)0000-0002-4123-0406 aut Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. Medication extraction Event classification Named entity recognition Transformer-architecture Idrissi-Yaghir, Ahmad verfasserin (orcid)0000-0003-1507-9690 aut Bewersdorff, Jeanette verfasserin (orcid)0000-0002-9091-2892 aut Frihat, Sameh verfasserin aut Friedrich, Christoph M. verfasserin (orcid)0000-0001-7906-0038 aut Zesch, Torsten verfasserin (orcid)0000-0002-9678-3825 aut Enthalten in Journal of biomedical informatics San Diego, Calif. : Academic Press, 2001 143 Online-Ressource (DE-627)334290791 (DE-600)2057141-0 (DE-576)104194502 1532-0480 nnns volume:143 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 44.32 Medizinische Mathematik medizinische Statistik VZ AR 143 |
| spelling |
10.1016/j.jbi.2023.104400 doi (DE-627)ELV060735686 (ELSEVIER)S1532-0464(23)00121-1 DE-627 ger DE-627 rda eng 330 004 570 VZ 44.32 bkl Schäfer, Henning verfasserin (orcid)0000-0002-4123-0406 aut Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. Medication extraction Event classification Named entity recognition Transformer-architecture Idrissi-Yaghir, Ahmad verfasserin (orcid)0000-0003-1507-9690 aut Bewersdorff, Jeanette verfasserin (orcid)0000-0002-9091-2892 aut Frihat, Sameh verfasserin aut Friedrich, Christoph M. verfasserin (orcid)0000-0001-7906-0038 aut Zesch, Torsten verfasserin (orcid)0000-0002-9678-3825 aut Enthalten in Journal of biomedical informatics San Diego, Calif. : Academic Press, 2001 143 Online-Ressource (DE-627)334290791 (DE-600)2057141-0 (DE-576)104194502 1532-0480 nnns volume:143 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 44.32 Medizinische Mathematik medizinische Statistik VZ AR 143 |
| allfields_unstemmed |
10.1016/j.jbi.2023.104400 doi (DE-627)ELV060735686 (ELSEVIER)S1532-0464(23)00121-1 DE-627 ger DE-627 rda eng 330 004 570 VZ 44.32 bkl Schäfer, Henning verfasserin (orcid)0000-0002-4123-0406 aut Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. Medication extraction Event classification Named entity recognition Transformer-architecture Idrissi-Yaghir, Ahmad verfasserin (orcid)0000-0003-1507-9690 aut Bewersdorff, Jeanette verfasserin (orcid)0000-0002-9091-2892 aut Frihat, Sameh verfasserin aut Friedrich, Christoph M. verfasserin (orcid)0000-0001-7906-0038 aut Zesch, Torsten verfasserin (orcid)0000-0002-9678-3825 aut Enthalten in Journal of biomedical informatics San Diego, Calif. : Academic Press, 2001 143 Online-Ressource (DE-627)334290791 (DE-600)2057141-0 (DE-576)104194502 1532-0480 nnns volume:143 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 44.32 Medizinische Mathematik medizinische Statistik VZ AR 143 |
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10.1016/j.jbi.2023.104400 doi (DE-627)ELV060735686 (ELSEVIER)S1532-0464(23)00121-1 DE-627 ger DE-627 rda eng 330 004 570 VZ 44.32 bkl Schäfer, Henning verfasserin (orcid)0000-0002-4123-0406 aut Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. Medication extraction Event classification Named entity recognition Transformer-architecture Idrissi-Yaghir, Ahmad verfasserin (orcid)0000-0003-1507-9690 aut Bewersdorff, Jeanette verfasserin (orcid)0000-0002-9091-2892 aut Frihat, Sameh verfasserin aut Friedrich, Christoph M. verfasserin (orcid)0000-0001-7906-0038 aut Zesch, Torsten verfasserin (orcid)0000-0002-9678-3825 aut Enthalten in Journal of biomedical informatics San Diego, Calif. : Academic Press, 2001 143 Online-Ressource (DE-627)334290791 (DE-600)2057141-0 (DE-576)104194502 1532-0480 nnns volume:143 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 44.32 Medizinische Mathematik medizinische Statistik VZ AR 143 |
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10.1016/j.jbi.2023.104400 doi (DE-627)ELV060735686 (ELSEVIER)S1532-0464(23)00121-1 DE-627 ger DE-627 rda eng 330 004 570 VZ 44.32 bkl Schäfer, Henning verfasserin (orcid)0000-0002-4123-0406 aut Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. Medication extraction Event classification Named entity recognition Transformer-architecture Idrissi-Yaghir, Ahmad verfasserin (orcid)0000-0003-1507-9690 aut Bewersdorff, Jeanette verfasserin (orcid)0000-0002-9091-2892 aut Frihat, Sameh verfasserin aut Friedrich, Christoph M. verfasserin (orcid)0000-0001-7906-0038 aut Zesch, Torsten verfasserin (orcid)0000-0002-9678-3825 aut Enthalten in Journal of biomedical informatics San Diego, Calif. : Academic Press, 2001 143 Online-Ressource (DE-627)334290791 (DE-600)2057141-0 (DE-576)104194502 1532-0480 nnns volume:143 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-MAT GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 44.32 Medizinische Mathematik medizinische Statistik VZ AR 143 |
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Schäfer, Henning @@aut@@ Idrissi-Yaghir, Ahmad @@aut@@ Bewersdorff, Jeanette @@aut@@ Frihat, Sameh @@aut@@ Friedrich, Christoph M. @@aut@@ Zesch, Torsten @@aut@@ |
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medication event extraction in clinical notes: contribution of the wispermed team to the n2c2 2022 challenge |
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Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge |
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In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. |
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In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. |
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In this work, we describe the findings of the ‘WisPerMed’ team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all mentions of medications from the clinical notes, and (ii) event classification, which involves classifying the medication mentions based on whether a change in the medication has been discussed. |
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|
| score |
7.400216 |