[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121073-en":3,"doc-seo-121073-105":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":20,"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},121073,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","Developing Machine Learning and Time-Series Analysis Methods with Applications in Diverse Fields - Doctor of Philosophy Dissertation","This dissertation develops machine learning and time-series analysis methods and demonstrates their utility across diverse applications. The work includes a risk-adjusted CUSUM control chart for monitoring readmission rate after PTBD catheter placement, with data preparation, risk prediction via logistic regression and tree-based models, rigorous model comparison, and chart evaluation. It also proposes multilayer modeling approaches for wide-range chemical concentration prediction from spectroscopic data, addressing high dimensionality and non-linearity and evaluating multiple regression-based layers.","Virginia Commonwealth University  \nVCU Scholars Compass  \n\n| Theses and Dissertations | Graduate School |\n| --- | --- |\n| 2024\u003Cbr>Developing Machine Learning and Time-Series Analysis Methods with Applications in Diverse Fields\u003Cbr>Muhammed Aljifri\u003Cbr>Virginia Commonwealth University\u003Cbr>Follow this and additional works at: [https://scholarscompass.vcu.edu/etd](https://scholarscompass.vcu.edu/etd)\u003Cbr> Part of the Chemical Engineering Commons, Data Science Commons, Mathematics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Risk Analysis Commons, and the Statistics and Probability Commons\u003Cbr>© Muhammed Aljifri |  |\n\nDownloaded from  \n[https://scholarscompass.vcu.edu/etd/7691](https://scholarscompass.vcu.edu/etd/7691)  \nThis Dissertation is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [libcompass@vcu.edu](libcompass@vcu.edu).  \n©Muhammed Aljifri, May 2024 All Rights Reserved.  \ni  \nDISSERTATION ON DEVELOPING MACHINE LEARNING AND TIME-SERIES ANALYSIS METHODS WITH APPLICATIONS IN DIVERSE FIELDS  \nA Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Virginia Commonwealth University.  \nby  \nMUHAMMED ALJIFRI  \nB.S. , King Abdulaziz University, KSA-2011  \nM.S. , Western Michigan University-2018  \nDirector: Yanjun Qian,  \nAssistant Professor, Department of Statistical Sciences and Operations Research  \nVirginia Commonwewalth University  \nRichmond, Virginia  \nMay, 2024  \nii  \nAcknowledgements  \nFirst, I would like to thank God for the boundless love, mercy, and grace, which have been my guiding lights in every challenging moment.  \nI want to express my deepest appreciation to my Ph.D. advisor, Dr. Yanjun Qian, whose guidance has been a beacon of light throughout this journey. His expertise and dedication to excellence have profoundly influenced my research approach, teaching me the value of persistence and precision. I sincerely thank my committee members, Dr. QiQi Lu, Dr. Ye Chen, and Dr. Abdel-Salam Gomaa, for their invaluable contributions [to my Ph.D. work. I am particularly thankful](to my Ph.D. work. I am particularly thankful) to Dr. QiQi Lu and Dr. Mo Li for the detailed feedback and enriching discussions that have notably improved the fourth chapter of my dissertation. Furthermore, the suggestions and feedback from Dr. Ye Chen have been instrumental in enhancing the quality of the third chapter.  \nI also want to express my heartfelt thanks to my parents, Zain and Safiyh, for their unwavering support and the incredible love they have shown me. I am truly blessed to be part of such a caring and supportive family.  \nI cannot express enough gratitude to my wife, Shahad, for her endless love and support, which have been my strength. My daughter, Aya, and my son, Ammar, have been a light in our lives, bringing unparalleled joy and laughter. Without the constant support of my family, I surely wouldn’t be where I am today.  \nTABLE OF CONTENTS  \nChapter Page  \nAcknowledgements ................................ iii  \nTable of Contents ................................ iv  \nList [of Tables](of Tables ................................... vi)[ ...................................](of Tables ................................... vi)[ vi](of Tables ................................... vi)  \n[List of Figures](List of Figures .................................)[ .................................](List of Figures .................................). viii  \nAbstract ..................................... xi  \n1 Introduction ................................. 1  \n2 Machine Learning based Risk adjusted CUSUM control chart for Monitoring Readmission Rate following PTBD Catheter Placement ...... 6  \n2.1 Introduction .............................. 6  \n2.2 Data and Methods ....","cbCaiurwFIT2NUXh","https://ap.wps.com/l/cbCaiurwFIT2NUXh","pdf",2202597,1,128,"English","en",105,"# Acknowledgements\n# Table of Contents\n# List of Tables\n# List of Figures\n# Abstract\n# Introduction\n# Machine Learning based Risk adjusted CUSUM control chart for Monitoring Readmission Rate following PTBD Catheter Placement\n## Introduction\n## Data and Methods\n## Results and Discussions\n## Conclusions\n# Multilayer Modeling for Wide-Range Chemical Concentration Prediction in Spectroscopic\n## Introduction\n## Matrials and Methods\n## Results and Discussion\n## Conclusions","[{\"question\":\"What risk monitoring method does the dissertation develop for clinical outcomes?\",\"answer\":\"It develops a machine learning based risk-adjusted CUSUM control chart to monitor readmission rate following PTBD catheter placement, including data preparation, risk prediction, and control chart evaluation.\"},{\"question\":\"How does the dissertation perform risk prediction for the CUSUM control chart?\",\"answer\":\"Risk prediction is performed using machine learning models including logistic regression and tree-based models, followed by model comparison to select and assess predictive performance.\"},{\"question\":\"What modeling approach is proposed for chemical concentration prediction from spectroscopic data?\",\"answer\":\"It proposes multilayer modeling methods, including principal component regression and partial least squares, along with dynamical layered regression (DLR) and classified layered regression (CLR), with tuning and comparative evaluation.\"}]","Developing Machine Learning and Time-Series Analysis Methods with Applications in Diverse Fields - Doctor of Philosophy Dissertation | PDF",1785733595,323,{"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},"developing-machine-learning-and-time-series-analysis-methods-with-applications-in-diverse-fields-doctor-of-philosophy-dissertation","",{"@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/developing-machine-learning-and-time-series-analysis-methods-with-applications-in-diverse-fields-doctor-of-philosophy-dissertation/121073/",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":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What risk monitoring method does the dissertation develop for clinical outcomes?","Question",{"text":75,"@type":76},"It develops a machine learning based risk-adjusted CUSUM control chart to monitor readmission rate following PTBD catheter placement, including data preparation, risk prediction, and control chart evaluation.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the dissertation perform risk prediction for the CUSUM control chart?",{"text":80,"@type":76},"Risk prediction is performed using machine learning models including logistic regression and tree-based models, followed by model comparison to select and assess predictive performance.",{"name":82,"@type":73,"acceptedAnswer":83},"What modeling approach is proposed for chemical concentration prediction from spectroscopic data?",{"text":84,"@type":76},"It proposes multilayer modeling methods, including principal component regression and partial least squares, along with dynamical layered regression (DLR) and classified layered regression (CLR), with tuning and comparative evaluation.","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},[93,97,101,105,110,115,120,123,128,131,135],{"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":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},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"]