[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120477-en":3,"doc-seo-120477-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120477,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","2nd International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics - Preface","Preface to a volume built on selected contributions from the 2nd International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics (WMLQ2024), held in Warsaw from June 4–7, 2024. The workshop, organized by the National Centre for Nuclear Research with international academic partners, fostered interdisciplinary exchange between physics, medicine, and computational science. Rapid advances in ML and QC are framed through quantum simulations, quantum algorithms, and classical/quantum machine learning applications, spanning HPC infrastructures, quantum ML platforms, cybersecurity, and medical high-throughput transcriptome profiling, with additional coverage in physics and astrophysics data analysis.","Computer Science • 26(SI) 2025 [https://doi.org/10.7494/csci.2025.26.SI.0001](https://doi.org/10.7494/csci.2025.26.SI.0001)  \nCitation  \nCopyright  \nWojciech Krzemie´n Konrad Klimaszewski Lech Raczy´nski  \nPREFACE:  \n2ND INTERNATIONAL WORKSHOP  \nON MACHINE LEARNING AND QUANTUM COMPUTING APPLICATIONS IN MEDICINE AND PHYSICS  \nComputer Science 26(SI) 2025: 5–8  \n© 2025 Author(s) . This is an open access publication, which can be used, distributed and reproduced in any medium according to the Creative Commons CC-BY 4.0 License.  \nPreface: 2nd International Workshop on Machine Learning and Quantum Computing. . . 7  \nPreface  \nThe articles in this volume are based on selected contributions to the 2nd International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics (WMLQ2024 [1]), which took place in Warsaw from June 4 to June 7, 2024. Organized by the National Centre for Nuclear Research (NCBJ) in collaboration with scientists from the University of Vienna, Jagiellonian University, and the Polish National Competence Centre in HPC Phase 2 (EuroCC2), this workshop served asa platform to incite knowledge exchange and interdisciplinary collaboration at the intersection of physics, medicine, and computational sciences.  \nWith the rapid advancement of machine learning (ML) and quantum computing (QC), new opportunities continue to emerge for solving complex problems in diverse fields, including medical imaging, radiotherapy, and fundamental physics. WMLQ2024 brought together leading researchers and practitioners to discuss cuttingedge developments in quantum simulations, quantum algorithms, and both classical and quantum machine learning techniques.  \nThis volume reflects the breadth and depth of research presented at the workshop, covering a wide range of topics, from advances in High-Performance Computing (HPC) such as AI-driven cloud infrastructures for scientific computing [2], platform for quantum machine learning models [7], and artificial intelligence in cybersecurity [5] to AI applications to high-throughput data in medicine in particular transcriptome profiling for disease research [3] . Additional sessions dedicated to advances in computational analysis and machine learning applications in physics and astrophysics were held at the workshop. Notably, contributions to this volume include discussions on muon bundle reconstruction in neutrino detectors [4], astrophysical data analysis [8], and the optimization of time-of-flight resolution in positron emission tomography [6] .  \nThe contributions collected here underscore the interdisciplinary nature of modern computational research and its impact on scientific discovery and technological innovation. We hope that this volume will serve as a valuable resource for researchers, engineers, and practitioners interested in the evolving frontiers of machine learning and quantum computing in Medicine and Physics.  \nWe extend our sincere gratitude to all the participants, speakers, and contributors who made WMLQ2024 a success, as well as to the organizing institutions for their dedication and support. We also acknowledge the reviewers for their efforts in ensuring the high quality of the papers included in this volume. We wish to acknowledge the support of the Polish Ministry of Education and Science in the frame of the “Doskonala Nauka II” programme (KONF/SN/0294/2023/01) . The project was co-financed by the National Centre for Research and Development in the frame of the European High-Performance Computing Joint Undertaking (JU) programme under grant agreement No 101101903 . The JU receives support from the Digital Europe Programme and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland,  \nPortugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg, Slovakia, Norway, T¨urkiye, Republic of North Macedonia, Iceland, Montenegro, Serbia.  \n","cbCaipYvSgzjb2lh","https://ap.wps.com/l/cbCaipYvSgzjb2lh","pdf",27374587,1,4,"English","en",105,"# Preface\n## Workshop background and organization\n## Key research directions: ML and quantum computing\n## Scope of this volume: medicine, physics, and computational innovation\n## Acknowledgements and funding\n## References","[{\"question\":\"What workshop does this preface introduce and where was it held?\",\"answer\":\"The preface introduces the 2nd International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics (WMLQ2024), held in Warsaw from June 4 to June 7, 2024.\"},{\"question\":\"Which research areas does the volume highlight?\",\"answer\":\"It highlights applications and advances including quantum simulations and algorithms, classical and quantum machine learning, HPC infrastructures, quantum ML platforms, cybersecurity methods, and medical transcriptome profiling, plus computational analysis in physics and astrophysics.\"},{\"question\":\"How is this volume connected to WMLQ2024?\",\"answer\":\"The articles in the volume are based on selected contributions to WMLQ2024 and reflect the breadth of research presented at the workshop across interdisciplinary themes.\"}]","2nd International Workshop on Machine Learning and Quantum Computing Applications in Medicine and Physics - 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