Negation Scope Delimitation in Clinical Text Using Three Approaches: NegEx; PyConTextNLP and SynNeg. - Hideyuki Tanushi; Hercules Dalianis; Martin Duneld; Maria Kvist; Maria Skeppstedt; Sumithra Velupillai (NODALIDA, 2013)

Detection of Healthcare-Associated Urinary Tract Infection in Swedish Electronic Health Records. - Hideyuki Tanushi; Maria Kvist; Elda Sparrelid (InMed, 2014)

HokuMed in NTCIR-11 MedNLP-2: Automatic Extraction of Medical Complaints from Japanese Health Records Using Machine Learning and Rule-based Methods. - Magnus Ahltorp; Hideyuki Tanushi; Shiho Kitajima; Maria Skeppstedt; Rafal Rzepka; Kenji Araki (NTCIR, 2014)

Detecting hospital-acquired infections: A document classification approach using support vector machines and gradient tree boosting. - Claudia Ehrentraut; Markus Ekholm; Hideyuki Tanushi; Jörg Tiedemann; Hercules Dalianis (Health Informatics J., 2018)

Terminology Expansion with Prototype Embeddings: Extracting Symptoms of Urinary Tract Infection from Clinical Text. - Mahbub Ul Alam 001; Aron Henriksson; Hideyuki Tanushi; Emil Thiman; Pontus Nauclér; Hercules Dalianis (HEALTHINF, 2021)

Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data. - Naoto Kai; Tomoki Yoshihisa; Toshiki Shimbaru; Hideto Yano; Hideyuki Tanushi (3PGCIC, 2023)

A Method for Constructing Research Data Provenance in High-Performance Computing Systems. - Yuta Namiki; Takeo Hosomi; Hideyuki Tanushi; Akihiro Yamashita; Susumu Date (e-Science, 2023)

Towards Development of University-wide Data Aggregation and Management Infrastructure for Research Data Utilization. - Hideyuki Tanushi; Hiroshi Furutani; Takeo Hosomi; Naoto Kai; Kaname Harumoto; Susumu Date (e-Science, 2024)

SCUP-HPC: System for Constructing and Utilizing Provenance on High-Performance Computing Systems. - Yuta Namiki; Takeo Hosomi; Hideyuki Tanushi; Akihiro Yamashita; Susumu Date (IEEE Access, 2025)