{"title":"认知计算在加强创新医疗解决方案中的作用","authors":"Abid Haleem, Mohd Javaid","doi":"10.1016/j.abst.2024.08.002","DOIUrl":null,"url":null,"abstract":"<div><p>Cognitive computing represents a groundbreaking development in healthcare, encompassing technological platforms that emulate the human brain's functionality. While cloud computing offers on-demand internet access to computing resources and services, cognitive computing focuses on modelling human mental processes to tackle complicated issues. Cognitive computing enhances human decision-making by integrating reasoning, machine learning, speech, natural language processing (NLP), and human-computer interaction. In the healthcare sector, it facilitates the analysis of clinical and genetic data to forecast diseases, tailor therapies, and elevate drug development. Additionally, it combines data analysis with adaptive page displays to tailor content based on the audience. Relevant papers in cognitive computing for healthcare were identified and studied. This paper aims to undertake an extensive scopic review of the pertinent literature from various sources, including articles and documents from numerous journals and conference proceedings. It delves into the need for cognitive computing in healthcare, elucidates supportive technologies, and expounds on its features within the healthcare domain. Furthermore, it identifies and discusses the substantial applications of cognitive computing in healthcare. These systems utilise computer models to replicate human cognitive processes, streamlining administrative tasks through artificial intelligence and cognitive computing. As a result, healthcare administrators can allocate more of their valuable time to patient care. Cognitive computing enhances outcomes and practitioner productivity and improves treatment decisions. The self-learning system of cognitive computing relies on real-time patient data, medical transcripts, and other pertinent information. These technologies can reduce the administrative burden on healthcare workers by automating tasks such as invoicing, claims processing, and appointment scheduling. This technology is poised to become increasingly indispensable in precision medicine.</p></div>","PeriodicalId":72080,"journal":{"name":"Advances in biomarker sciences and technology","volume":"6 ","pages":"Pages 152-165"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543106424000139/pdfft?md5=cb7d5fbc41d9253461511cb165aed156&pid=1-s2.0-S2543106424000139-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Role of cognitive computing in enhancing innovative healthcare solutions\",\"authors\":\"Abid Haleem, Mohd Javaid\",\"doi\":\"10.1016/j.abst.2024.08.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Cognitive computing represents a groundbreaking development in healthcare, encompassing technological platforms that emulate the human brain's functionality. While cloud computing offers on-demand internet access to computing resources and services, cognitive computing focuses on modelling human mental processes to tackle complicated issues. Cognitive computing enhances human decision-making by integrating reasoning, machine learning, speech, natural language processing (NLP), and human-computer interaction. In the healthcare sector, it facilitates the analysis of clinical and genetic data to forecast diseases, tailor therapies, and elevate drug development. Additionally, it combines data analysis with adaptive page displays to tailor content based on the audience. Relevant papers in cognitive computing for healthcare were identified and studied. This paper aims to undertake an extensive scopic review of the pertinent literature from various sources, including articles and documents from numerous journals and conference proceedings. It delves into the need for cognitive computing in healthcare, elucidates supportive technologies, and expounds on its features within the healthcare domain. Furthermore, it identifies and discusses the substantial applications of cognitive computing in healthcare. These systems utilise computer models to replicate human cognitive processes, streamlining administrative tasks through artificial intelligence and cognitive computing. As a result, healthcare administrators can allocate more of their valuable time to patient care. Cognitive computing enhances outcomes and practitioner productivity and improves treatment decisions. The self-learning system of cognitive computing relies on real-time patient data, medical transcripts, and other pertinent information. These technologies can reduce the administrative burden on healthcare workers by automating tasks such as invoicing, claims processing, and appointment scheduling. This technology is poised to become increasingly indispensable in precision medicine.</p></div>\",\"PeriodicalId\":72080,\"journal\":{\"name\":\"Advances in biomarker sciences and technology\",\"volume\":\"6 \",\"pages\":\"Pages 152-165\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2543106424000139/pdfft?md5=cb7d5fbc41d9253461511cb165aed156&pid=1-s2.0-S2543106424000139-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in biomarker sciences and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2543106424000139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in biomarker sciences and technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2543106424000139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Role of cognitive computing in enhancing innovative healthcare solutions
Cognitive computing represents a groundbreaking development in healthcare, encompassing technological platforms that emulate the human brain's functionality. While cloud computing offers on-demand internet access to computing resources and services, cognitive computing focuses on modelling human mental processes to tackle complicated issues. Cognitive computing enhances human decision-making by integrating reasoning, machine learning, speech, natural language processing (NLP), and human-computer interaction. In the healthcare sector, it facilitates the analysis of clinical and genetic data to forecast diseases, tailor therapies, and elevate drug development. Additionally, it combines data analysis with adaptive page displays to tailor content based on the audience. Relevant papers in cognitive computing for healthcare were identified and studied. This paper aims to undertake an extensive scopic review of the pertinent literature from various sources, including articles and documents from numerous journals and conference proceedings. It delves into the need for cognitive computing in healthcare, elucidates supportive technologies, and expounds on its features within the healthcare domain. Furthermore, it identifies and discusses the substantial applications of cognitive computing in healthcare. These systems utilise computer models to replicate human cognitive processes, streamlining administrative tasks through artificial intelligence and cognitive computing. As a result, healthcare administrators can allocate more of their valuable time to patient care. Cognitive computing enhances outcomes and practitioner productivity and improves treatment decisions. The self-learning system of cognitive computing relies on real-time patient data, medical transcripts, and other pertinent information. These technologies can reduce the administrative burden on healthcare workers by automating tasks such as invoicing, claims processing, and appointment scheduling. This technology is poised to become increasingly indispensable in precision medicine.