[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127088-en":3,"doc-seo-127088-105":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},127088,5909887256941,"Levi","https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc",7,"Healthcare","Smart Medicine - The Role of Artificial Intelligence and Machine Learning in Next-Generation Healthcare Innovation","Smart Medicine focuses on how big data and healthcare analytics in pharmaceuticals create both opportunity and complexity for next-generation healthcare products. The work summarizes benefits of machine learning and big data across healthcare systems while addressing real-world demands from patients and professionals, disease volume, drug insufficiency, and compliance with regulations and ethical guidelines. It also discusses opportunities and challenges for healthcare companies, research efforts, and infrastructure, culminating in a vision of personalized, smart medicine guided by legal and ethical frameworks.","Smart Medicine: The Role of Artificial Intelligence and Machine Learning in  \nNext-Generation Healthcare Innovation  \nRamanakar Reddy Danda1, Zakera Yasmeen2, Gowtham Mandala3, Kiran Kumar Maguluri4,  \nPambala ganesh5  \n1IT architect, CNH, NC,  \n2Data engineering lead Microsoft,  \n3Research Student  \n4IT systems Architect, Cigna Plano,  \n5Integration lead  \nKEYWORDS  \nArtificial Intelligence (AI), Machine Learning  \n(ML),Healthcare Innovation, Precision Medicine, Predictive Analytics, HealthTech, Personalized Healthcare, Clinical Decision Support Systems  \nABSTRACT  \nThe paper focuses on big data and healthcare pharmaceuticals, which pose both great promise and challenge as they can contribute to well-being and deliver innovation and knowledge to next-generation healthcare products. This paper provides an overview of the benefits that machine learning and big data technology contribute to healthcare systems. Realities such as patient and healthcare professional demands, the number of diseases, insufficient drugs, regulations, legal and ethical guideline restrictions, modus operandi, and technology development take place in the healthcare sector. In addition, big data opportunities and challenges for healthcare companies, research, and healthcare infrastructure are discussed. Finally, a vision of health innovation through personalized medicines as well as smart medicine is presented as a step closer to patients through regulatory, legal, and ethical guidelines, applications, and opportunities that need to be regulated and resolved.  \n(CDSS),Medical Data Analysis, AI-driven  \n Diagnostics.   \n1. Introduction  \nThe field of medicine has made significant progress in using patient data, not only to discover the root causes of diseases but also to assist in the development of new drugs, distinguish which strains are treatable and curable, and provide a system of regular healthcare to patients. However, the increasing computational power combined with the ability to find patterns and relationships in data has allowed scientists in recent years to create better models based on patient data. In this chapter, we look at some of the recent developments in patient management using machine learning, and then we will explore some of the smart patient solutions that heal the patient, with a specific focus on image processing using machine learning for tumor detection. After that, we discuss the creation of new models or upgrades of the existing ones for a battery of tests and develop cheaper and faster techniques. In the next section, we describe the disease prediction systems and the disease risk prediction system. The development model details the classification problem and the different models used. We discuss the different datasets used and provide an analysis of the dataset. We then detail what the different variables represent, and next, we implement a monitoring system. Since we implemented this model, we carried out a detailed validation on the test set and then trained the model. After that, we look at the comparison between the different models that have been used, and in the end, we give a summary of this work followed by the conclusions.Recent advancements in medicine, driven by the increasing computational power and the ability to analyze large volumes of patient data, have significantly enhanced our understanding of diseases and improved patient care. Machine learning (ML) has played a crucial role in this progress, particularly in developing predictive models, drug discovery, and personalized treatment plans. In this chapter, we explore how machine learning has transformed patient management, with a particular focus on image processing for tumor detection. By leveraging machine learning algorithms to analyze medical images, scientists and healthcare professionals can now detect tumors with greater accuracy and speed, enabling earlier and more effective interventions. We also discuss the creation and refinement of disease predi","cbCair5vnhmsZ1Rd","https://ap.wps.com/l/cbCair5vnhmsZ1Rd","pdf",293046,1,11,"English","en",105,"# Introduction\n## Background and Significance\n## Machine Learning in Patient Management","[{\"question\":\"How does machine learning improve patient management and healthcare innovation?\",\"answer\":\"Machine learning helps discover patterns in patient data, supports predictive models, and enables more accurate and faster detection, including image processing for tumor detection. It also assists in developing and refining disease prediction models and personalized treatment plans.\"},{\"question\":\"What challenges does the document highlight for applying AI and big data in healthcare?\",\"answer\":\"It emphasizes limitations such as regulations, legal and ethical guideline restrictions, insufficient drugs, and operational realities in healthcare. It also discusses challenges for healthcare companies, research, and infrastructure.\"},{\"question\":\"What role do electronic medical records (EMR/EHR) play in the proposed systems?\",\"answer\":\"The document states that ongoing predictive clinical decisions and personalized monitoring require comprehensive, low-cost data from all relevant medical events. This includes electronic medical record information, prescriptions, diagnostic and therapeutic procedures, lab results, medications, and behavioral or lifestyle counseling.\"}]","Smart Medicine - The Role of Artificial Intelligence and Machine Learning in Next-Generation Healthcare Innovation | PDF",1785936780,28,{"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},"smart-medicine-the-role-of-artificial-intelligence-and-machine-learning-in-next-generation-healthcare-innovation","",{"@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/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/smart-medicine-the-role-of-artificial-intelligence-and-machine-learning-in-next-generation-healthcare-innovation/127088/",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","2026-08-22","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},"How does machine learning improve patient management and healthcare innovation?","Question",{"text":76,"@type":77},"Machine learning helps discover patterns in patient data, supports predictive models, and enables more accurate and faster detection, including image processing for tumor detection. It also assists in developing and refining disease prediction models and personalized treatment plans.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What challenges does the document highlight for applying AI and big data in healthcare?",{"text":81,"@type":77},"It emphasizes limitations such as regulations, legal and ethical guideline restrictions, insufficient drugs, and operational realities in healthcare. It also discusses challenges for healthcare companies, research, and infrastructure.",{"name":83,"@type":74,"acceptedAnswer":84},"What role do electronic medical records (EMR/EHR) play in the proposed systems?",{"text":85,"@type":77},"The document states that ongoing predictive clinical decisions and personalized monitoring require comprehensive, low-cost data from all relevant medical events. This includes electronic medical record information, prescriptions, diagnostic and therapeutic procedures, lab results, medications, and behavioral or lifestyle counseling.","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},[94,98,102,106,111,116,119,124,129,132,136],{"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":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",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"]