TY - GEN
T1 - Pathomorphological Diagnosis Process Intelligence
AU - Pańkowska, Małgorzata
AU - Żytniewski, Mariusz
AU - Kozak, Mateusz
AU - Tomaszek, Krzysztof
AU - Spinczyk, Dominik
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Business process management is oriented towards improving processes to best support people, who are working in them. Recent innovations in the area of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and distributed systems have provided opportunities for new technologies applications, including process automation. This paper aims at the pathomorphological diagnosis (PD) process modeling for the ML solution implementation. The research method covers the PD laboratory case study. Authors argue that the PD process requires detailed analysis for its digitalization, automation, and combining with ML applications. Authors presented PD process models in BPMN notation, including laboratory equipment and emphasizing data and ML algorithms which are to be utilized in PD process digitalization for appropriate diagnosis for patients. Authors have found and emphasized that implementation of ML/AI algorithms is strongly based on fundamental process modeling.
AB - Business process management is oriented towards improving processes to best support people, who are working in them. Recent innovations in the area of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and distributed systems have provided opportunities for new technologies applications, including process automation. This paper aims at the pathomorphological diagnosis (PD) process modeling for the ML solution implementation. The research method covers the PD laboratory case study. Authors argue that the PD process requires detailed analysis for its digitalization, automation, and combining with ML applications. Authors presented PD process models in BPMN notation, including laboratory equipment and emphasizing data and ML algorithms which are to be utilized in PD process digitalization for appropriate diagnosis for patients. Authors have found and emphasized that implementation of ML/AI algorithms is strongly based on fundamental process modeling.
KW - BPMN
KW - Business Canvas Model
KW - Digital Image Analysis
KW - Enterprice Architecture
KW - Machine Learning
KW - Pathomorphology Diagnosis
KW - Process Intelligence
KW - Process Modeling
UR - https://www.scopus.com/pages/publications/105013617674
U2 - 10.1007/978-3-031-93580-0_8
DO - 10.1007/978-3-031-93580-0_8
M3 - Conference contribution
AN - SCOPUS:105013617674
SN - 9783031935794
T3 - Lecture Notes in Business Information Processing
SP - 176
EP - 196
BT - Information Technology for Management
A2 - Ziemba, Ewa Wanda
A2 - Chmielarz, Witold
A2 - Watróbski, Jaroslaw
PB - Springer Science and Business Media Deutschland GmbH
T2 - Topical Area of Information Technology for Business and Society, ITBS 2024, and the Thematic Track on Information System Management, ISM 2024, held as part of the 19th Conference on Computer Science and Intelligence Systems, FedCSIS 2024
Y2 - 8 September 2024 through 11 September 2024
ER -