[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123221-en":3,"doc-seo-123221-105":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":4,"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},123221,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","Bigdata Analysis of Pesticide Poisoning in Rural Worker Using Machine Learning Algorithm","Escalating pesticide exposure among rural and farm workers makes early detection and diagnosis of poisoning critical to initiate medical intervention and prevent long-term complications. To address limited diagnostic access to advanced equipment in rural communities, the research proposes a data-driven supervised machine learning approach using clinical and biochemical markers. The study’s key contribution is a systematic DRC–SML framework that guides a complete data science workflow from data collection and preprocessing through model selection, performance evaluation, and deployment readiness.","International Journal of Innovative Research in Science  \nEngineering and Technology (IJIRSET)  \n(A Monthly, Peer Reviewed, Refereed, Scholarly Indexed, Open Access Journal)  \nImpact Factor: 8.699 Volume 14, Issue 4 , April 2025  \nBigdata Analysis of Pesticide Poisoning in Rural Worker Using Machine Learning Algorithm  \nPatnana Chandramouli, Pachipenta Supraja, Penta Indumathi, Kinthali Sarat Kumar,  \nMarada Lakshmi Prasanna  \nUG Scholar, Dept. of Computer Science Engineering (Artificial Intelligence and Data Science), Satya Institute of  \nTechnology and Management, Vizianagaram, India  \nSeepana Ratna Kumari  \nAssistant Professor, Dept. of Computer Science Engineering (Artificial Intelligence and Data Science), Satya Institute  \nof Technology and Management, Vizianagaram, India  \nABSTRACT: It is in recent times that the working conditions of the rural and farm workers have drawn special attention on account of escalating exposure to toxins like pesticides. Detection and diagnosis of pesticide poisonings atthe initial stages become crucial to save the patient at the earliest stage of medical interventions and to forestall longterm complications. Even so, few rural communities still lack access to high-tech equipment and techniques in diagnostics. To resolve this problem, this project introduces a data-driven methodology using Supervised Machine Learning (SML) methods for the efficient and accurate diagnosis of pesticide poisoning using clinical and biochemical markers. The main contribution of this research is the development and application of a systematic methodology called Data Refinement Cycle with Supervised Machine Learning (DRC–SML) . This model was created to offer a complete, applicable, and reproducible methodology that directs a Data Science project from start to finish. It consists of phases like data collection, data preprocessing, missing value handling, encoding and scaling, model selection, performance metrics, and preparation for deployment. In contrast to most current methodologies, which only deal with isolated phases ofthe data pipeline, DRC–SML guarantees an overall workflow that facilitates a smooth transition between the steps and uniform results.  \nKEYWORDS: Data Science, Supervised Learning, Data Refinement, Pesticide Poisoning, Rural Healthcare, Machine Learning, Rough Set Theory, Decision Rules, Healthcare Diagnostics  \nI. INTRODUCTION  \nThe use of data science and machine learning in healthcare has grown significantly in recent years, especially in terms of enhancing decision-making and diagnostic precision. Predictive models can be revolutionary in public health, which is one of the many fields where these methods are showing promise. Pesticide poisoning is one of the major health problems that rural labourers, especially those employed in the agricultural industry, encounter. Serious health effects, such as acute poisoning and persistent long-term disorders, can result from pesticide exposure, whether it occurs by ingesting, skin contact, or inhalation.  \nReducing the negative impacts of pesticide exposure requires early diagnosis and prompt action. among order to diagnose pesticide toxicity among rural labourers, this research suggests using a supervised learning model. The algorithm will be taught to categorise and forecast the risk of pesticide poisoning in people who work in rural agricultural settings by utilising a combination of clinical data, environmental exposure measures, and health-related markers. Historical data on workers exposed to pesticides and experiencing different levels of poisoning symptoms will be analysed using supervised learning, more especially classification algorithms. In rural healthcare settings, where resources are frequently scarce and prompt diagnosis may significantly impact patient outcomes, the aim of this research is to develop an accurate and efficient diagnostic tool that can be implemented. By giving medical professionals insightful information and facilita","cbCailOU9kx57Lph","https://ap.wps.com/l/cbCailOU9kx57Lph","pdf",1907516,1,10,"English","en",105,"# I. INTRODUCTION\n## Background and problem context\n## Proposed supervised learning approach and target model\n# II. RELATED WORK","[{\"question\":\"Why is early detection of pesticide poisoning important for rural workers?\",\"answer\":\"Early-stage detection enables prompt medical intervention and helps avoid long-term complications caused by acute poisoning and persistent disorders.\"},{\"question\":\"What data sources does the proposed model use for diagnosis?\",\"answer\":\"The supervised learning model is trained using clinical data, biochemical markers, and measures related to environmental exposure along with worker information.\"},{\"question\":\"What is the main contribution of the research besides using machine learning algorithms?\",\"answer\":\"The research introduces DRC–SML, a data refinement cycle framework that provides an end-to-end, reproducible workflow across the full data pipeline rather than handling isolated steps.\"}]","Bigdata Analysis of Pesticide Poisoning in Rural Worker Using Machine Learning Algorithm | PDF",1785815301,25,{"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},"bigdata-analysis-of-pesticide-poisoning-in-rural-worker-using-machine-learning-algorithm","",{"@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/bigdata-analysis-of-pesticide-poisoning-in-rural-worker-using-machine-learning-algorithm/123221/",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","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is early detection of pesticide poisoning important for rural workers?","Question",{"text":75,"@type":76},"Early-stage detection enables prompt medical intervention and helps avoid long-term complications caused by acute poisoning and persistent disorders.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What data sources does the proposed model use for diagnosis?",{"text":80,"@type":76},"The supervised learning model is trained using clinical data, biochemical markers, and measures related to environmental exposure along with worker information.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the main contribution of the research besides using machine learning algorithms?",{"text":84,"@type":76},"The research introduces DRC–SML, a data refinement cycle framework that provides an end-to-end, reproducible workflow across the full data pipeline rather than handling isolated steps.","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},[93,97,101,105,110,115,120,123,128,131,134],{"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":21,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":21,"slug":133},"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]