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pMineR & pMinShiny TUTORIAL

Jun 12 / Mon - 08:30-13:00, AIME 2023, Portoroz, Slovenia

pMineR & pMinShiny

R libraries for Process Mining for Healthcare

The pMineR project was born in 2016 and presented the first time at AIME 2016, in Vienna. We are glad for the opportunity to be here now to present the current state of this never-ending development, share visions and perspective and collects all the potential contributes of users and interested colleagues.

pMineR is an R library specifically designed to support Process Analysts to work in the clinical domain, providing Process Discovery algorithms, tools for Conformance Checking, Trace and Event Log analysis and methods for representing and working with Clinical Guidelines, Consensus flow, Clinical Protocols, etc.. The library implements those features considering the most frequent statistical tools used in healthcare, such as non-parametric tests (Chi-Square, Fisher's Exact test), Surivival Analysis (Kaplan Meier curves, log-rank tests) and also Machine Learning methods and predictors to estimate the most relevant clinical outcomes in terms of events or times. For more info, visit : https://github.com/PMLiquidLab/pMineR.v046

pMinShiny is a Shiny-based Graphical User Interface designed to create a confortable environment for quick data esploration using pMineR. It quickly allows lo load Event Log and see some descriptive stats about traces, perform queries; discovery processes, analyze the temporal evolution of numeric attributes (e.g. lab exams) and build simple but communicative Logistic Regressor-based Predictive models. For more info, visit: https://github.com/PMLiquidLab/pMinShiny

The TUTORIAL

This Tutorial is designed to provide a general overwiew on pMineR, and introduce the partecipants to the main modules, by short hands-on sessions, to cope with Process Discovery, Conformance Checking and Statistical Analysis of paths, events and timing. The Tutorial will also exploit invited speakers to present their experience on real-world data analysis and open projects based on pMineR. Finally, an open round-table will be the opportunity to share opinions, ideas about the topic or a further evolution of the libraries. An indicative program is shonw below :

Frontal Lesson Modules ( 1h 30' ):

General introduction
Event Log data Loading, internal structure, events, time ( pMineR::dataLoader() )
Performing queries and Quality-of-data oriented trace inspection ( pMineR::QOD() )
Process Discovery with First Order Markov Models and CareFlow Miner ( pMineR::firstOrderMarkovModel() and pMineR::CareFlowMiner() )
Clinical Guideline Conformance Checking with Pseudo Workflow language ( pMineR::confCheck_easy() )
pMinShiny : a Graphical User Interface for a quick'n dirty (and time saver!) first look

Short lectures ( 1h ):

Hospital Datawarehouse and sustainable computational pipeline:
- Carlotta Masciocchi and Mariachiara Savino. The case of Poiclinico Gemelli of Rome
- Michel Cuendet. The case of the Centre Hospitalier Universitaire Vaudoise (CHUV), Lausanne
Real-world Process Discovery
- Olivier Michielin. A differential process mining analysis of COVID-19 management for cancer patients
- Federico Mastroleo. Facing the "what went wrong?" in treatments organization/delivery in Radiotherapy
Real-world Conformance Checking
- Stefania Orini. Clinical Guideline modeling with PWL for Mild Cognitive Impairment
- Giovanni Frisoni and Cristina Festari. Design and implementation of a Process Oriented Multicentric-clinical study

Round Table ( 30' ):

Freewheeling discussion about the current issues or future opportunities of the discipline and/or the project. For esample: empowering the PD with more ML? PD-oriented scheduling and planning DSS, are they possible? Engaging MDs: winning and losing strategies? PM4HC and Semantic web technologies: which possible marriage? Big Data = Big Problems: can we scale PM analysis? Federated PM to cope with Patient's privacy and data ownership, in multicentric clinical studies? .... and any other Wild and Crazy ideas!

pMineR/pMinShiny frontal lesson

50%

Real-world use cases, presented by invited speakers

30%

Round Table, interactive open discussion

20%

Tavazzi E, Gatta R, Vallati M, Cotti Piccinelli S, Filosto M, Padovani A, Castellano M, Di Camillo B. Leveraging process mining for modeling progression trajectories in amyotrophic lateral sclerosis. BMC Med Inform Decis Mak. 2023 Feb 2;22(Suppl 6):346. doi: 10.1186/s12911-023-02113-7. PMID: 36732801; PMCID: PMC9896660.
Dagliati A, Gatta R, Malovini A, Tibollo V, Sacchi L, Cascini F, Chiovato L, Bellazzi R (2022). A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data. FRONTIERS IN PUBLIC HEALTH, vol. 10, ISSN: 2296-2565, doi: 10.3389/fpubh.2022.815674
Cuendet MA, Gatta R, Wicky A, Gerard CL, Dalla-Vale M, Tavazzi E, Michielin G, Delyon J, Ferahta N, Cesbron J, Lofek S, Huber A, Jankovic J, Demicheli R, Bouchaab H, Digklia A, Obeid M, Peters S, Eicher M, Pradervand S, Michielin O (2022). A differential process mining analysis of COVID-19 management for cancer patients. FRONTIERS IN ONCOLOGY, vol. 12, ISSN: 2234-943X, doi: 10.3389/fonc.2022.1043675
Placidi L, Boldrini L, Lenkowicz J, Manfrida S, Gatta R, Damiani A, Chiesa S, Ciellini F, Valentini V (2021). Process mining to optimize palliative patient flow in a high-volume radiotherapy department. TECHNICAL INNOVATIONS & PATIENT SUPPORT IN RADIATION ONCOLOGY, vol. 17, p. 32-39, ISSN: 2405-6324, doi: 10.1016/j.tipsro.2021.02.005
Tavazzi E, Gerard C L, Michielin O, Wicky A, Gatta R, Cuendet MA (2021). A Process Mining Approach to Statistical Analysis: Application to a Real-World Advanced Melanoma Dataset. In: Lecture Notes in Business Information Processing. LECTURE NOTES IN BUSINESS INFORMATION PROCESSING, vol. 406, p. 291-304, Springer Science and Business Media Deutschland GmbH, ISBN: 978-3-030-72692-8, ISSN: 1865-1348, 2020, doi: 10.1007/978-3-030-72693-5_22
Lenkowicz J, Gatta R, Masciocchi C, Casa C, Cellini F, Damiani A, Dinapoli N, Valentini V (2018). Assessing the conformity to clinical guidelines in oncology: An example for the multidisciplinary management of locally advanced colorectal cancer treatment. MANAGEMENT DECISION, vol. 56, p. 2172-2186, ISSN: 0025-1747, doi: 10.1108/MD-09-2017-0906
Gatta R, Vallati M, Lenkowicz J, Casa C, Cellini F, Damiani A, Valentini V (2018). A framework for event log generation and knowledge representation for process mining in healthcare. In: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. PROCEEDINGS - INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, vol. 2018-, p. 647-654, IEEE Computer Society, ISBN: 978-1-5386-7449-9, ISSN: 1082-3409, grc, 2018, doi: 10.1109/ICTAI.2018.00103
Gatta R, Vallati M, Lenkowicz J, Rojas E, Damiani A, Sacchi L, De Bari B, Dagliati A, Fernandez-Llatas C, Montesi M, Marchetti A, Castellano M, Valentini V (2017). Generating and comparing knowledge graphs of medical processes using pMineR. In: Proceedings of the Knowledge Capture Conference, K-CAP 2017. p. 1-4, Association for Computing Machinery, Inc, ISBN: 9781450355537, usa, 2017, doi: 10.1145/3148011.3154464
Gatta R, Lenkowicz J, Vallati M, Rojas E, Damiani A, Sacchi L, De Bari B, Dagliati A, Fernandez-Llatas C, Montesi M, Marchetti A, Castellano M, Valentini V (2017). pMineR: An innovative R library for performing process mining in medicine. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, vol. 10259, p. 351-355, Springer Verlag, ISBN: 978-3-319-59757-7, ISSN: 0302-9743, aut, 2017, doi: 10.1007/978-3-319-59758-4_42

Planet Earth
Email: roberto.gatta.bs@gmail.com

Swing by for a cup of :)


Department of Clinical and Experimental Sciences, Università degli Studi di Brescia (IT) Precision Oncology Center, Department of Oncology, Lausanne University Hospital, Lausanne, Switzerland (CH)	Department of Information Engineering, Università degli Studi di Padova (IT)	Department of Electrical, Computer and Biomedical Engineering at the University of Pavia (IT).	Department of Industrial and Information Engineering, Università degli Studi di Pavia (IT)	School of Computing and Engineering, University of Huddersfield (UK).

Jun 12 / Mon - 08:30-13:00, AIME 2023, Portoroz, Slovenia

pMineR & pMinShiny

The TUTORIAL

Tutorial Chairs

Program Committee

Supporting Associations


The projects are now hosted on the gitHub area of the PMLiquidLab, a Liquid Lab (geographically distributed, cross-institutional and underground movment) lab of passionate researchers in the field of Process Mining for Healthcare. For more info, please visit: ( https://github.com/PMLiquidLab)	The initiative is kindly endorsed and sponsored by SIBIM, the Italian Scientific Society of Biomedical Informatics : https://www.sibim.it/