[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119237-en":3,"doc-seo-119237-105":30,"detail-sidebar-cat-0-en-105":91},{"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},119237,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",7,"Healthcare","1st. Joint DFH/UFA workshop on AI in Medicine - Optimised Trials with Machine Learning","This document introduces the 1st Joint DFH/UFA workshop on AI in Medicine under the 4EU+ European University Alliance, organized jointly by Sorbonne University and Heidelberg University. Held from September 11–13, 2024, the three-day program gathers machine learning researchers for an exchange on applying machine learning to randomised clinical studies. The focus is on improving statistical insights for interventions and diagnostic procedures, supported by presentations from leading researchers across participating institutions. It also outlines the planned audience and acknowledges academic and staff support.","Publication Series:  \nJoint DFH/UFA workshop on AI in Medicine  \nXavier Fresquet, Jürgen Hesser (eds. )  \n1st. Joint DFH/UFA workshop on AI in Medicine: Optimised Trials with Machine Learning  \nAbstract  \nSorbonne University and Heidelberg University join forces to organise the first workshop on AI in medicine under the 4EU+ European University Alliance.  \nThe aim of the three-day workshop, held from September 11th to 13th 2024, is to bring together researchers in the field of machine learning for an information exchange in the field of Artificial Intelligence in Medicine. The topic of the first workshop is \"Optimised Trials with Machine Learning\" . This involves the use of machine learning methods in randomised clinical studies in order to obtain better statistical information about interventions or diagnostic procedures. Recent progress in this field is presented by internationally recognized researchers from Sorbonne and Heidelberg but also from other institutions such as the 4EU+ Alliance member universities.  \nThe audience comprise a diverse group of PhD and Master students from the fields of medicine, biology, and computer science.  \nAcknowledgements  \nThe editors would like to thank the Deutsch-Französische Hochschule / Université franco-allemande (DFH/UFA) to fund this workshop, and all the staff from both universities who contributed to the success of the event with their commitment.  \nCite as  \nXavier Fresquet, Jürgen Hesser (2024): 1st. Joint DFH/UFA workshop on AI in Medicine: Optimised Trials with Machine Learning. Heidelberg University Library.  \n[https://doi.org/10.11588/heidok.00035481](https://doi.org/10.11588/heidok.00035481)  \nPublished by Heidelberg University Library, 2024  \nThe electronic version of this work is permanently available on:  \n[https://archiv.ub.uni-heidelberg.de/volltextserver/](https://archiv.ub.uni-heidelberg.de/volltextserver/)  \ndoi: [https://doi.org/10.11588/heidok.00035481](https://doi.org/10.11588/heidok.00035481)  \nText © 2024, Xavier Fresquet, Jürgen Hesser  \n1st . Joint DFH/UFA workshop on AI in Medicine  \nContents  \n1 Christoph Blattgerste, J¨urgen Hesser, Cleo-Aron Weis (Heidelberg): Extending the margin of pathological tissue using a computer vision pipeline 4  \n2 Marcus Buchwald, Pascal Memmesheimer, Arash Dooghaie Moghadam, Ines Tuschner, Laura Alejandra Santamaria Suarez, Jimmy Daza, Timo Itzel, Christoph Antoni, Catherina Gerhards, Micheal Neumaier, Christoph Brochhausen, Peter R. Galle, Matthias Ebert, Arndt Weinmann, J¨urgen Hesser, Vincent Heuveline, Andreas Teufel (Heidelberg): Dis  \ncovering predictive biomarkers for liver staging using machine learning methods 9  \n3 Anna Kabo (Prague): Ethical issues in the use of artificial intelligence in medicine 15  \n4 Elaheh Mosaieby, Michael Michal (Prague): Epigenetic Signatures in Sarcoma: Unveiling Subtype-Specific Methylation Patterns 17  \n5 Sara Monji Azad, Marvin Kinz, Jyot Makadiya, David M¨aannle, Claudia Scherl, J¨urgen Hesser (Heidelberg): An Assessment of Non-Rigid Point Cloud Registration Methods on Two Novel Soft Tissue Deformation Datasets 22  \n6 Tobias Meißner, Werner Nahm, J¨urgen Hesser (Heidelberg): Accuracy and Precision of 3D Reconstruction Methods for Localizing Point-Like Gamma Sources with a Coded Aperture Camera 26  \n7 Bacem K. Othman, Ilmo Leivo, Alena Sk´alov´a (Prague): Artificial Computational Pathology May Refine and Redefine Salivary Gland Tumor Entities: A Molecular Bioinformatic Perspective 31  \n8 Pooja Mali Rai (Milan): WIRELESS INTRAORAL ELECTRONICS INTEGRATED WITH  \nAI FOR DISEASE DIAGNOSIS 34  \n9 Andrei Sirazitdinov, Jonas Tesarz, J¨urgen Hesser (Heidelberg): Treatment Group Assignment using Data from PerPain RCT 39  \n10 Ishita Singhal, Bocca Giorgio, Giuseppe Maurizio Facchi, Jacopo Burger (Milan): Revolutionizing Dental Care: Harnessing Artificial Intelligence and Deep Learning for Early Caries Detection and Pathology Analysis 43  \n11 Abhinay Krishna Vellala, Moritz Schnitzer, Alexander Herte","cbCaiifsnLJBcW5M","https://ap.wps.com/l/cbCaiifsnLJBcW5M","pdf",7631872,1,55,"English","en",105,"# Contents\n## Extending the margin of pathological tissue using a computer vision pipeline\n## Discovering predictive biomarkers for liver staging using machine learning methods\n## Ethical issues in the use of artificial intelligence in medicine\n## Epigenetic Signatures in Sarcoma: Unveiling Subtype-Specific Methylation Patterns\n## An Assessment of Non-Rigid Point Cloud Registration Methods on Two Novel Soft Tissue Deformation Datasets\n## Accuracy and Precision of 3D Reconstruction Methods for Localizing Point-Like Gamma Sources with a Coded Aperture Camera\n## Artificial Computational Pathology May Refine and Redefine Salivary Gland Tumor Entities: A Molecular Bioinformatic Perspective\n## Wireless Intraoral Electronics Integrated with AI for Disease Diagnosis\n## Treatment Group Assignment using Data from PerPain RCT\n## Revolutionizing Dental Care: Harnessing Artificial Intelligence and Deep Learning for Early Caries Detection and Pathology Analysis\n## Automated Radiology Report Generation from Radiologist Impressions using Fine-Tuned LLAMA-3 Model: A Novel Approach\n## Enhancing Tumor Site Prediction through Integrated Somatic Mutation Sequencing and Genomic Positional Encoding","[{\"question\":\"What is the theme of the 1st Joint DFH/UFA workshop on AI in Medicine?\",\"answer\":\"The workshop focuses on “Optimised Trials with Machine Learning,” emphasizing the use of machine learning methods in randomised clinical studies to improve statistical information for interventions and diagnostic procedures.\"},{\"question\":\"When and where is the workshop held?\",\"answer\":\"The three-day workshop is held from September 11th to 13th, 2024, as organized by Sorbonne University and Heidelberg University under the 4EU+ Alliance.\"},{\"question\":\"Who is the target audience for the workshop?\",\"answer\":\"The audience includes PhD and Master students from medicine, biology, and computer science, alongside researchers presenting recent advances.\"}]","1st. Joint DFH/UFA workshop on AI in Medicine - Optimised Trials with Machine Learning | PDF",1785723248,139,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"1st-joint-dfhufa-workshop-on-ai-in-medicine-optimised-trials-with-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/1st-joint-dfhufa-workshop-on-ai-in-medicine-optimised-trials-with-machine-learning/119237/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the theme of the 1st Joint DFH/UFA workshop on AI in Medicine?","Question",{"text":75,"@type":76},"The workshop focuses on “Optimised Trials with Machine Learning,” emphasizing the use of machine learning methods in randomised clinical studies to improve statistical information for interventions and diagnostic procedures.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"When and where is the workshop held?",{"text":80,"@type":76},"The three-day workshop is held from September 11th to 13th, 2024, as organized by Sorbonne University and Heidelberg University under the 4EU+ Alliance.",{"name":82,"@type":73,"acceptedAnswer":83},"Who is the target audience for the workshop?",{"text":84,"@type":76},"The audience includes PhD and Master students from medicine, biology, and computer science, alongside researchers presenting recent advances.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,118,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":116,"slug":117},40,"healthcare",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},8,"Research & Report",30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]