1.
Borchert, F., Llorca, I., Schapranow, M.-P.: Cross-Lingual Candidate Retrieval and Re-ranking for Biomedical Entity Linking. In: Arampatzis, A., Kanoulas, E., Tsikrika, T., Vrochidis, S., Giachanou, A., Li, D., Aliannejadi, M., Vlachos, M., Faggioli, G., en Ferro, N. (reds.) Experimental IR Meets Multilinguality, Multimodality, and Interaction. bll. 135–147. Springer Nature Switzerland, Cham (2023).
2.
Nordmeyer, S., Kraus, M., Ziehm, M., Kirchner, M., Schafstedde, M., Kelm, M., Niquet, S., Stephen, M., Baczko, I., Knosalla, C., Schapranow, M.-P., Dittmar, G., Gotthardt, M., Falcke, M., Regitz-Zagrosek, V., Kuehne, T., Mertins, P.: Disease- and sex-specific differences in patients with heart valve disease: A proteome study. Life Sci Alliance. 6, e202201411 (2023).
3.
Budde, K., Hiltawsky, K., Eskofier, B., Heismann, B., Kirchner, E., Klevesath, M., Lang, M., Loskill, H., Neumuth, T., Schapranow, M.-P., Schmidt-Rumposch, A., Susec, B., Welskop-Deffaa, E.M., Wolf-Ostermann, K.: KI für Gesundheitsfachkräfte: Chancen und Herausforderungen von medizinischen und pflegerischen KI-Anwendungen. Plattform Lernende Systeme (2023).
4.
Schapranow, M.-P., Borchert, F., Bougatf, N., Hund, H., Eils, R.: Software-Tool Support for Collaborative, Virtual, Multi-Site Molecular Tumor Boards. SN Computer Science. 4, 358 (2023).
5.
Kämmer, N., and Borchert, F., and Winkler, S., and de Melo, G., and Schapranow, M.-P.: Resolving Elliptical Compounds in German Medical Text. The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks. bll. 292–305. Association for Computational Linguistics, Toronto, Canada (2023).
6.
Llorca, I., Borchert, F., Schapranow, M.-P.: A Meta-dataset of German Medical Corpora: Harmonization of Annotations and Cross-corpus NER Evaluation. Proceedings of the 5th Clinical Natural Language Processing Workshop. bll. 171–181. Association for Computational Linguistics, Toronto, Canada (2023).
7.
Steinwand, S., Borchert, F., Winkler, S., Schapranow, M.-P.: GGTWEAK: Gene Tagging with Weak Supervision for German Clinical Text. In: Juarez, J.M., Marcos, M., Stiglic, G., en Tucker, A. (reds.) Artificial Intelligence in Medicine. bll. 183–192. Springer Nature Switzerland, Cham (2023).
8.
Schapranow, M.-P.: Lernende Laborsysteme: Wie kann künstliche Intelligenz im Labor unterstützen?. In: Raem, A.M. en Rauch, P. (reds.) Immunoassays: ergänzende Methoden, Troubleshooting, regulatorische Anforderungen. bll. 755–775. Springer Berlin Heidelberg, Berlin, Heidelberg (2023).
9.
Borchert, F., Llorca, I., Roller, R., Arnrich, B., Schapranow, M.-P.: xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization. arXiv preprint arXiv:2310.11275. (2023).
10.
Borchert, F., Llorca, I., Schapranow, M.-P.: HPI-DHC @ BC8 SympTEMIST Track: Detection and Normalization of Symptom Mentions with SpanMarker and xMEN. In: Islamaj, R., Arighi, C., Campbell, I., Gonzalez-Hernandez, G., Hirschman, L., Krallinger, M., Lima-López, S., Weissenbacher, D., en Lu, Z. (reds.) Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models. , New Orleans, LA (2023).
11.
Fox, S., Preiß, M., Borchert, F., Rasheed, A., Schapranow, M.-P.: HPIDHC at NTCIR-17 MedNLP-SC: Data Augmentation and Ensemble Learning for Multilingual Adverse Drug Event Detection. NTCIR 17 Conference: Proceedings of the 17th NTCIR Conference on Evaluation of Information Access Technologies. bll. 185–192. , Tokyo, Japan (2023).
12.
Schapranow, M.-P., Bayat, M., Rasheed, A., Naik, M., Graf, V., Schmidt, D., Budde, K., Cardinal, H., Sapir-Pichhadze, R., Fenninger, F., Sherwood, K., Keown, P., Günther, O., Pandl, K., Leiser, F., Thiebes, S., Sunyaev, A., Niemann, M., Schimanski, A., Klein, T.: NephroCAGE—German-Canadian Consortium on AI for Improved Kidney Transplantation Outcome: Protocol for an Algorithm Development and Validation Study. JMIR Res Protoc 2023. 12, (2023).
13.
Schapranow, M.-P.: Kann uns ChatGPT bei der Digitalisierung der Medizin helfen?. Management & Krankenhaus. 42, 10 (2023).
14.
Schapranow, M.-P.: NephroCAGE: Wie Künstliche Intelligenz bei Nierenversagen unterstützen kann. Gesundhyte: Forschung neu vernetzen. 15, 100—102 (2023).