{"title":"基于群体的非传染性疾病人工智能解决方案临床验证框架","authors":"Kitty Kioskli, Spyridon Papastergiou, Theofanis Fotis","doi":"10.55708/js0209001","DOIUrl":null,"url":null,"abstract":": Non-communicable diseases (NCDs) present complex challenges in patient care. Artificial Intelligence (AI) offers transformative potential, but its implementation requires addressing key issues. This study proposes a swarm intelligence-inspired clinical validation framework for NCDs, promoting openness, trustworthiness, and continuous self-validation. The framework creates a collaborative environment, connecting healthcare entities, patients, caregivers, and professionals. The swarm-based approach enhances diagnostic accuracy, enables personalized treatment, improves prognosis, supports clinical decision-making, engages patients, enables real-time monitoring, and promotes continuous learning. These implications have the power to revolutionize NCD management and improve patient outcomes.","PeriodicalId":484451,"journal":{"name":"Journal of Engineering Research and Sciences","volume":"124 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Swarm-Based Clinical Validation Framework of Artificial Intelligence Solutions for Non-Communicable Diseases\",\"authors\":\"Kitty Kioskli, Spyridon Papastergiou, Theofanis Fotis\",\"doi\":\"10.55708/js0209001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Non-communicable diseases (NCDs) present complex challenges in patient care. Artificial Intelligence (AI) offers transformative potential, but its implementation requires addressing key issues. This study proposes a swarm intelligence-inspired clinical validation framework for NCDs, promoting openness, trustworthiness, and continuous self-validation. The framework creates a collaborative environment, connecting healthcare entities, patients, caregivers, and professionals. The swarm-based approach enhances diagnostic accuracy, enables personalized treatment, improves prognosis, supports clinical decision-making, engages patients, enables real-time monitoring, and promotes continuous learning. These implications have the power to revolutionize NCD management and improve patient outcomes.\",\"PeriodicalId\":484451,\"journal\":{\"name\":\"Journal of Engineering Research and Sciences\",\"volume\":\"124 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering Research and Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.55708/js0209001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Research and Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55708/js0209001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Swarm-Based Clinical Validation Framework of Artificial Intelligence Solutions for Non-Communicable Diseases
: Non-communicable diseases (NCDs) present complex challenges in patient care. Artificial Intelligence (AI) offers transformative potential, but its implementation requires addressing key issues. This study proposes a swarm intelligence-inspired clinical validation framework for NCDs, promoting openness, trustworthiness, and continuous self-validation. The framework creates a collaborative environment, connecting healthcare entities, patients, caregivers, and professionals. The swarm-based approach enhances diagnostic accuracy, enables personalized treatment, improves prognosis, supports clinical decision-making, engages patients, enables real-time monitoring, and promotes continuous learning. These implications have the power to revolutionize NCD management and improve patient outcomes.