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It highlights efficiency, decision support, and innovation enabled by advanced AI models, while surveying key frameworks such as TensorFlow, PyTorch, and Scikit-learn and their role in building intelligent systems. The review also analyzes ethics, privacy, and transparency concerns, emphasizing responsible AI deployment and how ChatGPT can improve human-machine communication for sustainable development across domains.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/ai-and-chatgpt-applications-in-computer-science-a-review-of-machine-learning-frameworks-for-healthcare-food-production-and-cybersecurity/128819/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/ai-and-chatgpt-applications-in-computer-science-a-review-of-machine-learning-frameworks-for-healthcare-food-production-and-cybersecurity/128819.png","ImageObject",300,407,{"name":92,"@type":93},"Maeve","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-19","2026-08-06",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What domains does the review focus on for AI and ChatGPT applications?","Question",{"text":113,"@type":114},"The review focuses on healthcare, food production, and cybersecurity, describing how AI can support diagnosis and disease management, optimize agricultural production and supply chains, and enhance threat sensing and protective systems.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which machine learning frameworks are mentioned as important for building AI systems?",{"text":118,"@type":114},"The review highlights TensorFlow, PyTorch, and Scikit-learn as key frameworks that help develop, deploy, and evaluate machine learning models efficiently at scale.",{"name":120,"@type":111,"acceptedAnswer":121},"What ethical and governance issues does the review emphasize for AI adoption?",{"text":122,"@type":114},"The review stresses concerns about data ethics, bias, privacy, and explainability, arguing that responsible development requires collaboration among computer scientists, policymakers, and domain experts.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},128819,1786003670,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":130,"read_time":145},2336474466712,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","| Volume 1: Issue 2 |  | Page: 57-74 |  |\n| --- | --- | --- | --- |\n| AI and ChatGPT Applications in Computer Science: A Review of Machine Learning Frameworks for Healthcare, Food Production, and Cybersecurity\u003Cbr>Alexandra Harry1*\u003Cbr>1Independent Researcher USA\u003Cbr>[1](1Alaxendraharry37@gmail.com)[Alaxendraharry37@gmail.com](1Alaxendraharry37@gmail.com) |  |  |  |\n| Submitted: 03/09/2025 | Accepted: 05/10/2025 |  | Published Online: 12/10/2025 |\n| Abstract\u003Cbr>The review presents the transformative uses of Artificial Intelligence (AI) and ChatGPT in the computer science in the context of machine learning frameworks applicable to healthcare, food production, and cybersecurity. It points out the efficiency, decision-making and innovation in these areas through advanced AI models. This paper talks about some of the most important frameworks, including TensorFlow, PyTorch, and Scikit-learn, and their contribution to creating intelligent systems. It further explores the ethical, privacy and transparency issues related to the inclusion of AI. This review identifies the role of responsible AI deployment and how ChatGPT may help to mediate human-machine communications in order to promote sustainable technological development in key areas by studying cross-domain effects.\u003Cbr>Key words\u003Cbr>AI, ChatGPT, Machine Learning, Healthcare, Food Production, Cybersecurity, Artificial Intelligence Frameworks, Data Privacy. |  |  |  |\n\n1. INTRODUCTION  \nOne of the most disruptive trends in the computer science of today has been Artificial Intelligence (AI) that is transforming industries due to its capability to resemble human intelligence and simplify the procedure of making complicated decisions. Healthcare, agriculture, cybersecurity, and education are just some examples, the AI technologies (especially, machine learning (ML) and deep learning (DL) technologies) have transformed the way data is analyzed, interpreted, and used [1] . The latest and one of the latest developments in the field of AI is ChatGPT, a sophisticated natural language processing (NLP) model created by OpenAI, which proves the potential of conversational AI, which is currently growing in both academic and industrial contexts [2] .  \nThe onset of AI in computer science has given a tremendous boost to its capability to solve problems such that the systems are able to learn by analyzing the data, identify patterns and make predictions more precisely. Machine learning systems like TensorFlow and PyTorch and Scikitlearn have turned out to be essential to researchers and developers to develop smart systems that can solve domain-specific problems. Along with the fact that they allow large-scale computation, they ensure flexibility in the development, deployment, and evaluation of models, which, in turn, makes AI applications more accessible and effective [3] .  \nChatGPT and other types of generative AI models have expanded the limits of machine intelligence in recent years by allowing humans and machines to communicate to each other in a natural and context-sensitive way. This development has created new opportunities to use AI to solve problems that are not necessarily based on conventional computational activities, such as health care, food production, and cybersecurity three essential areas that have a direct impact on the well-being and stability of people and society [4] . In the medical field, AI can be used to aid in the diagnostic image, disease management, and individualized treatment guidelines. Machine learning is applied in food production to optimize agricultural production, detect the health of crops, and manage supply chains. On the same note, AI-based systems have been used to increase the amount of threat sensing, initiate response to incidents automatically, and bolster electronic protective systems in the context of cybersecurity [5] .  \nNonetheless, the quick advance of AI and ChatGPT technologies also has certain issues to do with data ethics, bias, privacy, and e","cbCaiewcdVfadOSX","https://ap.wps.com/l/cbCaiewcdVfadOSX","pdf",1117495,18,"English","# Introduction\n# AI and ChatGPT Technologies","[{\"question\":\"What domains does the review focus on for AI and ChatGPT applications?\",\"answer\":\"The review focuses on healthcare, food production, and cybersecurity, describing how AI can support diagnosis and disease management, optimize agricultural production and supply chains, and enhance threat sensing and protective systems.\"},{\"question\":\"Which machine learning frameworks are mentioned as important for building AI systems?\",\"answer\":\"The review highlights TensorFlow, PyTorch, and Scikit-learn as key frameworks that help develop, deploy, and evaluate machine learning models efficiently at scale.\"},{\"question\":\"What ethical and governance issues does the review emphasize for AI adoption?\",\"answer\":\"The review stresses concerns about data ethics, bias, privacy, and explainability, arguing that responsible development requires collaboration among computer scientists, policymakers, and domain experts.\"}]","AI and ChatGPT Applications in Computer Science - A Review of Machine Learning Frameworks for Healthcare, Food Production, and Cybersecurity | PDF",45]