[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126860-en":3,"doc-seo-126860-105":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},126860,1099523882367,"Hazel","https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc",8,"Research & Report","Predicting Mitral Valve mTEER Surgery Outcomes Using Machine Learning and Deep Learning Techniques - Research Report","Mitral Transcatheter Edge-to-Edge Repair (mTEER) is used to treat mitral valve disorders, yet reliable prediction of procedural outcomes remains difficult. The paper develops a first-in-field approach that leverages both classical machine learning and deep learning. A dataset of 467 patients is compiled with labeled echocardiogram videos and patient reports including Transesophageal Echocardiography (TEE) measurements. Using this dataset, the study benchmarks six ML algorithms and two DL models, showing the promise of ML/DL for outcome prediction and enabling directions for future work.","Predicting Mitral Valve mTEER Surgery Outcomes Using Machine Learning and Deep Learning Techniques  \nTejas Vyas  \nToronto Metropolitan University Toronto, ON, Canada  \nMohsena Chowdhury  \nToronto Metropolitan University Toronto, ON, Canada  \nXiaojiao Xiao  \nToronto Metropolitan University Toronto, ON, Canada  \narXiv :2401 . 13197v1 [ ee ss .IV] 24 Jan 2024  \nMathias Claeys  \nSt. Michael’s Hospital-University of Toronto Toronto, ON, Canada  \nGéraldine Ong  \nSt. Michael’s Hospital-University of Toronto Toronto, ON, Canada  \nGuanghui Wang  \nToronto Metropolitan University Toronto, ON, Canada [wangcs@torontomu.ca](wangcs@torontomu.ca)  \nABSTRACT  \nMitral Transcatheter Edge-to-Edge Repair (mTEER) is a medical procedure utilized for the treatment of mitral valve disorders. However, predicting the outcome of the procedure poses a significant challenge. This paper makes the first attempt to harness classical machine learning (ML) and deep learning (DL) techniques for predicting mitral valve mTEER surgery outcomes. To achieve this, we compiled a dataset from 467 patients, encompassing labeled echocardiogram videos and patient reports containing Transesophageal Echocardiography (TEE) measurements detailing Mitral Valve Repair (MVR) treatment outcomes. Leveraging this dataset, we conducted a benchmark evaluation of six ML algorithms and two DL models. The results underscore the potential of ML and DL in predicting mTEER surgery outcomes, providing insight for future investigation and advancements in this domain.  \nKEYWORDS  \nmachine learning, deep learning, mitral valve, mTEER surgery.  \nACM Reference Format:  \nTejas Vyas, Mohsena Chowdhury, Xiaojiao Xiao, Mathias Claeys, Géraldine Ong, and Guanghui Wang. 2024. Predicting Mitral Valve mTEER Surgery Outcomes Using Machine Learning and Deep Learning Techniques. In Proceedings of Make sure to enter the correct conference title from your rights confirmation emai (Conference acronym ICMAI). ACM, New York, NY, USA, 5 pages. [https://doi.org/XXXXXXX.XXXXXXX](https://doi.org/XXXXXXX.XXXXXXX)  \n1 INTRODUCTION  \nThe mitral valve, one of four valves in the heart that keep blood flowing in the right direction, plays a pivotal role in the intricate orchestration of blood flow between the left atrium and the left ventricle. Among the spectrum of cardiac disorders, mitral valve prolapse stands out as a notable concern, often progressing to the widespread condition known as Mitral Valve Regurgitation (MVR) . Particularly prevalent among the elderly population, MVR presents  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions [from permissions@acm.org](from permissions@acm.org).  \nConference acronym ICMAI, May 10–12, 2024, Beijing, China © 2024 Association for Computing Machinery.  \nACM ISBN 978-1-4503-XXXX-X/18/06. . . $15.00 [https://doi.org/XXXXXXX.XXXXXXX](https://doi.org/XXXXXXX.XXXXXXX)  \na significant health challenge, severely impacting physiological functions and often necessitating surgical intervention [1] .  \nMitral Transcatheter Edge-to-Edge Repair (mTEER) emerges as a beacon of hope in the realm of cardiac surgery, offering a less invasive alternative to traditional open-heart procedures. This innovative surgical approach has proven to be a viable and effective option for patients dealing with MVR [3] . By avoiding the complexities and risks associated with open-heart surgery, mTEER minimizes the invasiveness of the intervention, promoting faster recovery and reduced postoperative complications. Howev","cbCaia3RGc4ZhELd","https://ap.wps.com/l/cbCaia3RGc4ZhELd","pdf",1055310,1,5,"English","en",105,"# Introduction\n# Related Work","[{\"question\":\"What is the main goal of the paper?\",\"answer\":\"To predict outcomes of mitral valve mTEER surgery using machine learning and deep learning based on echocardiogram video data and TEE measurements from patient reports.\"},{\"question\":\"What data was used to build the prediction models?\",\"answer\":\"The study compiled a dataset from 467 patients, including labeled echocardiogram videos and patient reports with Transesophageal Echocardiography (TEE) measurements describing mitral valve repair outcomes.\"},{\"question\":\"How were the models evaluated?\",\"answer\":\"The work benchmarks six classical ML algorithms and two deep learning models on the compiled dataset to assess their capability for predicting mTEER surgery outcomes.\"}]","Predicting Mitral Valve mTEER Surgery Outcomes Using Machine Learning and Deep Learning Techniques - Research Report | PDF",1785935275,13,{"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},"predicting-mitral-valve-mteer-surgery-outcomes-using-machine-learning-and-deep-learning-techniques-research-report","",{"@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/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/predicting-mitral-valve-mteer-surgery-outcomes-using-machine-learning-and-deep-learning-techniques-research-report/126860/",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","2026-08-05",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 main goal of the paper?","Question",{"text":75,"@type":76},"To predict outcomes of mitral valve mTEER surgery using machine learning and deep learning based on echocardiogram video data and TEE measurements from patient reports.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data was used to build the prediction models?",{"text":80,"@type":76},"The study compiled a dataset from 467 patients, including labeled echocardiogram videos and patient reports with Transesophageal Echocardiography (TEE) measurements describing mitral valve repair outcomes.",{"name":82,"@type":73,"acceptedAnswer":83},"How were the models evaluated?",{"text":84,"@type":76},"The work benchmarks six classical ML algorithms and two deep learning models on the compiled dataset to assess their capability for predicting mTEER surgery outcomes.","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},[93,97,101,105,109,114,119,122,127,130,134],{"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":21,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":21,"slug":137},19,"General","general"]