Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis...33rd Medical Informatics Europe Conference (MIE2023), May 22-25, 2023, Gothenburg, Sweden.

Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinica...

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Publicado en:Studies in Health Technology & Informatics Vol. 302; pp. 18 - 23
Autores principales: MARZANO, Luca, MEIJER, Sebastiaan, DAN, Asaf, TENDLER, Salomon, DE PETRIS, Luigi, LEWENSOHN, Rolf, RAGHOTHAMA, Jayanth, DARWICH, Adam S.
Formato: pictorial proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Application of Process Mining for Modelling Small Cell Lung Cancer Prognosis...33rd Medical Informatics Europe Conference (MIE2023), May 22-25, 2023, Gothenburg, Sweden.
      aug:
        au:
          MARZANO, Luca
          MEIJER, Sebastiaan
          DAN, Asaf
          TENDLER, Salomon
          DE PETRIS, Luigi
          LEWENSOHN, Rolf
          RAGHOTHAMA, Jayanth
          DARWICH, Adam S.
        affil: Division of Health Informatics and Logistics, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), KTH Royal Institute of Technology, Huddinge, Sweden
      sug:
        subj:
          Carcinoma, Small Cell Prognosis
          Lung Neoplasms Prognosis
          Lung Neoplasms Drug Therapy
          Chemotherapy, Cancer Methods
          Treatment Outcomes Evaluation
          Prediction Models
          Data Science
          Data Mining
          Congresses and Conferences Spain
          Spain
          Process Assessment (Health Care)
          Decision Making, Clinical
      ab: Process mining is a relatively new method that connects data science and process modelling. In the past years a series of applications with health care production data have been presented in process discovery, conformance check and system enhancement. In this paper we apply process mining on clinical oncological data with the purpose of studying survival outcomes and chemotherapy treatment decision in a real-world cohort of small cell lung cancer patients treated at Karolinska University Hospital (Stockholm, Sweden). The results highlighted the potential role of process mining in oncology to study prognosis and survival outcomes with longitudinal models directly extracted from clinical data derived from healthcare.
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        research
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      ougenre: Article
    language: English
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