[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126183-en":3,"doc-seo-126183-105":30,"detail-sidebar-cat-0-en-105":84},{"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":11,"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},126183,549768072016,"River Wang","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Quantum algorithms and complexity in healthcare applications - a systematic review with machine learning-optimized analysis","This study delivers a systematic review of quantum computing approaches applied to healthcare computational problems, emphasizing quantum-theoretical foundations and algorithmic complexity. An optimized literature-mining workflow combines Particle Swarm Optimization (PSO) with Latent Dirichlet Allocation (LDA) to analyze 63 peer-reviewed works. Findings reveal two dominant research directions: quantum computing for artificial intelligence in healthcare and quantum computing for healthcare data security, supported by gradient boosting classification with strong metrics and interpretability via LIME. Key opportunities and remaining challenges are identified.","TYPE Review  \nPUBLISHED 07 May 2025  \nDOI 10.3389/fcomp.2025.1584114  \nOPEN ACCESS  \nEDITED BY  \nStanislav Protasov,  \nInnopolis University, Russia  \nREVIEWED BY  \nOmar A. Alzubi,  \nAl-Balqa Applied University, Jordan Miodrag Zivkovic,  \nSingidunum University, Serbia Edgard Muñoz-Coreas,  \nUniversity of North Texas, United States  \n*CORRESPONDENCE  \nAgostino Marengo  \n [agostino. marengo@unifg.it](agostino. marengo@unifg.it)  \nRECEIVED 26 February 2025  \nACCEPTED 21 April 2025  \nPUBLISHED 07 May 2025  \nCITATION  \nMarengo A and Santamato V (2025) Quantum algorithms and complexity in healthcare applications: a systematic review with machine learning-optimized analysis.  \nFront. Comput. Sci. 7:1584114 .  \ndoi: 10.3389/fcomp.2025.1584114  \nCOPYRIGHT  \n© 2025 Marengo and Santamato. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nQuantum algorithms and complexity in healthcare applications: a systematic review with machine learning-optimized analysis  \nAgostino Marengo * and Vito Santamato  \nDepartment of Agriculture, Food, Natural Resources and Engineering Sciences, University of Foggia, Foggia, Italy  \nThis paper presents a systematic review of quantum computing approaches to healthcare-related computational problems, with an emphasis on quantum-theoretical foundations and algorithmic complexity. We adopt an optimized machine learning methodology—combining Particle Swarm Optimization (PSO) with Latent Dirichlet Allocation (LDA)—to analyze the literature and identify key research themes at the intersection of quantum computing and healthcare. A total of 63 peer-reviewed studies were analyzed, with 41 categorized under the first domain and 22 under the second. This approach revealed two primary research directions: (1) quantum computing for artificial intelligence in healthcare, and (2) quantum computing for healthcare data security. We highlight the theoretical advances underlying these domains, from novel quantum machine learning algorithms for biomedical data to quantum cryptographic protocols for securing medical information. A gradient boosting classifier further validates our taxonomy by reliably distinguishing between the two categories of research, demonstrating the robustness of the identified themes, with an accuracy of 84. 2%, a precision of 88.9%, a recall of 84. 2%, an F1-score of 84. 5%, and an area under the curve of 0.875. Interpretability analysis using Local Interpretable Model-Agnostic Explanations (LIME) exposes distinguishing features of each category (e. g., references to biomedical applications versus blockchain-based security frameworks), offering transparency into the literaturedriven categorization, with the latter showing the most significant contributions to topic assignment (ranging from −0.133 to +0 . 128) . Our findings underscore that quantum algorithms offer significant potential to enhance data security, optimize complex diagnostic computations, and provide computational speedups for health informatics. We also identify outstanding challenges—such as the need for scalable quantum algorithms and error-tolerant hardware integration—that must be addressed to translate these theoretical advancements into real-world clinical impact. This study emphasizes the importance of hybrid quantum-classical models and cross-disciplinary research to bridge the gap between cutting-edge quantum computing theory and its practical applications in healthcare.  \nKEYWORDS  \nquantum algorithms, computational complexity, quantum machine learning, Particle Swarm Optimization, healthcare data security  \nFrontiers in Computer Scien","cbCaim15E8bhdvbV","https://ap.wps.com/l/cbCaim15E8bhdvbV","pdf",2110691,1,30,"English","en",105,"# Introduction\n## Quantum computing foundations\n## Healthcare applications\n## Literature review approach\n## Findings and research directions\n## Validation and interpretability\n## Challenges and future work","[{\"question\":\"What challenges must be addressed for real-world clinical impact?\",\"answer\":\"The paper highlights the need for scalable quantum algorithms and error-tolerant hardware integration to translate theoretical advances into clinical use.\"}]","Quantum algorithms and complexity in healthcare applications - a systematic review with machine learning-optimized analysis | PDF",1785903653,76,{"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":79,"head_meta":81,"extra_data":83,"updated_unix":28},"quantum-algorithms-and-complexity-in-healthcare-applications-a-systematic-review-with-machine-learning-optimized-analysis","",{"@graph":36,"@context":78},[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/quantum-algorithms-and-complexity-in-healthcare-applications-a-systematic-review-with-machine-learning-optimized-analysis/126183/",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","2026-08-24","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":11},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72],{"name":73,"@type":74,"acceptedAnswer":75},"What challenges must be addressed for real-world clinical impact?","Question",{"text":76,"@type":77},"The paper highlights the need for scalable quantum algorithms and error-tolerant hardware integration to translate theoretical advances into clinical use.","Answer","https://schema.org",{"og:url":52,"og:type":80,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":82,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":85},[86,90,94,98,103,108,113,115,120,123,127],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":87,"show_sort_weight":88,"slug":89},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":91,"show_sort_weight":92,"slug":93},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Exam",70,"exam",{"id":99,"doc_module":4,"doc_module_name":46,"category_name":100,"show_sort_weight":101,"slug":102},5,"Comic",60,"comic",{"id":104,"doc_module":4,"doc_module_name":46,"category_name":105,"show_sort_weight":106,"slug":107},6,"Technology",50,"technology",{"id":109,"doc_module":4,"doc_module_name":46,"category_name":110,"show_sort_weight":111,"slug":112},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":21,"slug":114},"research-report",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},9,"Religion & Spirituality",20,"religion-spirituality",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":118,"slug":122},"World Cup","world-cup",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":124,"slug":126},10,"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":99,"slug":130},19,"General","general"]