[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127594-en":3,"doc-seo-127594-105":30,"detail-sidebar-cat-0-en-105":92},{"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},127594,549768064622,"Anda","https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8",8,"Research & Report","Causal Inference and Machine Learning Methods in Parkinson’s Disease Data Analysis - PhD dissertation","This PhD dissertation investigates Parkinson’s Disease using machine learning and causal inference methods. It presents a descriptive analysis of PD in a large, high-quality database and examines medication-related costs. The study evaluates the causal impact of Carbidopa-Levodopa on two-year survival using a doubly robust approach, and reports a small positive causal difference. It also conducts causal survival analyses for one- to five-year outcomes comparing no drug use versus Carbidopa-Levodopa, alongside demographic, comorbidity, and medication characterization after database cleaning.","Chapman University Digital Commons  \n\n| Computational and Data Sciences (PhD) Dissertations | Dissertations and Theses |\n| --- | --- |\n| Spring 8-2023\u003Cbr>Causal Inference and Machine Learning Methods in Parkinson's Disease Data Analysis\u003Cbr>Albert Pierce\u003Cbr>Chapman University, [alpierce@chapman.edu](alpierce@chapman.edu)\u003Cbr>Follow this and additional works at: [https://digitalcommons.chapman.edu/cads_dissertations](https://digitalcommons.chapman.edu/cads_dissertations)\u003Cbr> Part of the Data Science Commons |  |\n\nRecommended Citation  \nA. Pierce, \"Causal inference and machine learning methods in Parkinson's Disease data analysis,\" Ph. D. dissertation, Chapman University, Orange, CA, 2023. [https://doi.org/10.36837/chapman.000494](https://doi.org/10.36837/chapman.000494)  \nThis Dissertation is brought to you for free and open access by the Dissertations and Theses at Chapman University Digital Commons. It has been accepted for inclusion in Computational and Data Sciences (PhD) Dissertations by an authorized administrator of Chapman University Digital Commons. For more information, please contact [laughtin@chapman.edu](laughtin@chapman.edu).  \nCausal Inference and Machine Learning Methods in Parkinson’s Disease  \nData Analysis  \nA Dissertation by  \nAlbert Pierce  \nChapman University  \nOrange, CA  \nSchmid College of Science and Technology  \nSubmitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computational and Data Science  \nAugust 2023  \nCommittee in charge:  \nAdrian Vajiac, Ph.D.  \nSidy Danioko, Ph.D.  \nChair: Cyril Rakovski, Ph.D.  \nThe dissertation of Albert Pierce is approved.  \nAdrian Vajiac, Ph.D.  \nSidy Danioko, SD  \nSidy Danioko, Ph.D.  \nChair: Cyril Rakovski, Ph.D.  \nMay 2023  \nCausal Inference and Machine Learning Methods in Parkinson’s Disease Data Analysis  \nCopyright © 2023  \nby Albert Pierce  \nACKNOWLEDGEMENTS  \nI would like to thank everyone who has helped me throughout my journey and any assistance they have provided to me. I would like to thank Dr. Cyril Rakovski, my main advisor, for his guidance, expertise, and his undivided attention to my projects. I would also like to thank my parents for always supporting me throughout my journey and for giving me the best advice. Thankyou everyone for your help.  \nBest,  \nAlbert Pierce  \nLIST OF PUBLICATIONS  \n\n| Number | Publication |\n| --- | --- |\n| 1 | [https://doi.org/10.1016/j.cmpbup.2021.100028](https://doi.org/10.1016/j.cmpbup.2021.100028) |\n| 2 | [https://doi.org/10.1016/j.jpsychires.2023.01.032](https://doi.org/10.1016/j.jpsychires.2023.01.032) |\n\nABSTRACT  \nCausal Inference and Machine Learning Methods in Parkinson’s Disease Data Analysis  \nby Albert Pierce  \nThis dissertation documents an investigation into Parkinson’s Disease utilizing machine learning and causal inference methods. I will cover a descriptive analysis of Parkinson’s Disease (PD) in avast, high-quality database and present costs associated with Parkinson’s Disease medications. I also researched a causal inference method assessing the Carbidopa-Levodopa effect on two-year survival and a causal survival analysis on a one-to-five-year survival comparing no drug use and Carbidopa-Levodopa in Parkinson’s Disease patients.  \nFor my classification with Parkinson’s gait, patients were monitored with a smartphone and an additional 6 Inertial Measurement Unit (IMU) sensors to collect clinical gait measures. I used classical machine learning algorithms on raw smartphone data to distinguish between ON and OFF times. With an average accuracy of 92.5%, this work demonstrates the feasibility of using smartphone data to distinguish between ON versus OFF walking and lays the groundwork for areal-world, corrective feedback system.  \nI also researched the causal effect of the most prevalent PD medication in terms of survival. In particular, I focused on the probability of two-year survival with PD patients taking CarbidopaLevodopa and no drug use and assessing whether there w","cbCaigHuNGZnTfx5","https://ap.wps.com/l/cbCaigHuNGZnTfx5","pdf",3185927,1,88,"English","en",105,"# 1. Introduction\n# 2. Parkinson’s Disease\n## 2.1 What is Parkinson’s Disease?\n## 2.2 Demographics and Cost of Care in the United States\n## 2.3 Common Symptoms and Effects\n## 2.3.1 Tremors\n## 2.3.2 Rigidity","[{\"question\":\"What datasets and descriptive analyses are used in the dissertation?\",\"answer\":\"The dissertation uses a large, high-quality database (Cerner Real-World Data) covering patients diagnosed with Parkinson’s Disease from 2016 to 2022, after cleaning to form a cohort of 110,037 subjects, with analyses of demographics, comorbidities, and medications as well as medication costs.\"},{\"question\":\"How is Carbidopa-Levodopa’s effect on survival assessed?\",\"answer\":\"A causal inference method evaluates the Carbidopa-Levodopa effect on two-year survival using a doubly robust approach, and a subsequent causal survival analysis compares no drug use versus Carbidopa-Levodopa for one to five years.\"},{\"question\":\"How are machine learning methods applied to Parkinson’s gait data?\",\"answer\":\"For classification of Parkinson’s gait, patients are monitored with a smartphone plus additional inertial measurement unit (IMU) sensors to collect clinical gait measures. Classical machine learning algorithms on raw smartphone data distinguish ON versus OFF times, achieving an average accuracy of 92.5%.\"}]","Causal Inference and Machine Learning Methods in Parkinson’s Disease Data Analysis - PhD dissertation | PDF",1785940170,222,{"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":87,"head_meta":89,"extra_data":91,"updated_unix":28},"causal-inference-and-machine-learning-methods-in-parkinsons-disease-data-analysis-phd-dissertation","",{"@graph":36,"@context":86},[37,54,69],{"@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/causal-inference-and-machine-learning-methods-in-parkinsons-disease-data-analysis-phd-dissertation/127594/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What datasets and descriptive analyses are used in the dissertation?","Question",{"text":76,"@type":77},"The dissertation uses a large, high-quality database (Cerner Real-World Data) covering patients diagnosed with Parkinson’s Disease from 2016 to 2022, after cleaning to form a cohort of 110,037 subjects, with analyses of demographics, comorbidities, and medications as well as medication costs.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How is Carbidopa-Levodopa’s effect on survival assessed?",{"text":81,"@type":77},"A causal inference method evaluates the Carbidopa-Levodopa effect on two-year survival using a doubly robust approach, and a subsequent causal survival analysis compares no drug use versus Carbidopa-Levodopa for one to five years.",{"name":83,"@type":74,"acceptedAnswer":84},"How are machine learning methods applied to Parkinson’s gait data?",{"text":85,"@type":77},"For classification of Parkinson’s gait, patients are monitored with a smartphone plus additional inertial measurement unit (IMU) sensors to collect clinical gait measures. Classical machine learning algorithms on raw smartphone data distinguish ON versus OFF times, achieving an average accuracy of 92.5%.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]