Victor Owoyele, Gbonjubola Oyinlola Ogungbangbe, Jesutobiloba Oluwasami, Patrick Oluwole Abolarin, Maryam Tayo Ayinla
{"title":"The Role of Artificial Intelligence in Health Care.","authors":"Victor Owoyele, Gbonjubola Oyinlola Ogungbangbe, Jesutobiloba Oluwasami, Patrick Oluwole Abolarin, Maryam Tayo Ayinla","doi":"10.54548/njps.v39i1.1","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous aspects of AI have been incorporated into the healthcare delivery system. For instance, in disease diagnosis, the practice of personalised treatment plans and precision medicine are AI-dependent. This review gives a widespread role of AI in healthcare, with a focus on applications, and challenges. Deep brain stimulation, statistical analysis, machine learning, and deep learning are a few examples of AI-powered technologies that have contributed immensely to biomedical research and medical imaging advancement. Moreover, AI algorithms are pivotal in genomics research, easing the identification of genetic markers related to disease vulnerability and treatment reaction, thereby aiding the practice of precision medicine. Apart from diagnosis and treatment strategies, AI assists in healthcare management and resource optimization, along with the discovery and therapy of drugs. Forecasting of disease outbreaks, effective allocation of hospital resources, and management of patient traffic rely mostly on predictive analytics driven by AI. Again, AI-powered virtual health assistance, telemedicine has aided patient appointments and support, giving real-time support and health recommendations. Although AI algorithms provide outstanding breakthroughs in healthcare, AI adoption is cumbered by numerous dares such as monetary concerns, regulatory hurdles, data privacy fears, and ethical considerations associated with AI applications, such as algorithm bias and transparency. Futuristically, AI application in healthcare holds vast potential, such as early disease detection, drug discovery, and optimization of treatment. Concerted efforts targeted at tackling the prevailing challenges and creating holistic control would be important to tie together the full potential of AI in rejuvenating the healthcare delivery system.</p>","PeriodicalId":35043,"journal":{"name":"Nigerian Journal of Physiological Sciences","volume":"39 1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nigerian Journal of Physiological Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54548/njps.v39i1.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous aspects of AI have been incorporated into the healthcare delivery system. For instance, in disease diagnosis, the practice of personalised treatment plans and precision medicine are AI-dependent. This review gives a widespread role of AI in healthcare, with a focus on applications, and challenges. Deep brain stimulation, statistical analysis, machine learning, and deep learning are a few examples of AI-powered technologies that have contributed immensely to biomedical research and medical imaging advancement. Moreover, AI algorithms are pivotal in genomics research, easing the identification of genetic markers related to disease vulnerability and treatment reaction, thereby aiding the practice of precision medicine. Apart from diagnosis and treatment strategies, AI assists in healthcare management and resource optimization, along with the discovery and therapy of drugs. Forecasting of disease outbreaks, effective allocation of hospital resources, and management of patient traffic rely mostly on predictive analytics driven by AI. Again, AI-powered virtual health assistance, telemedicine has aided patient appointments and support, giving real-time support and health recommendations. Although AI algorithms provide outstanding breakthroughs in healthcare, AI adoption is cumbered by numerous dares such as monetary concerns, regulatory hurdles, data privacy fears, and ethical considerations associated with AI applications, such as algorithm bias and transparency. Futuristically, AI application in healthcare holds vast potential, such as early disease detection, drug discovery, and optimization of treatment. Concerted efforts targeted at tackling the prevailing challenges and creating holistic control would be important to tie together the full potential of AI in rejuvenating the healthcare delivery system.