{"title":"Transforming Healthcare in Low-Resource Settings With Artificial Intelligence: Recent Developments and Outcomes.","authors":"Ravi Rai Dangi, Anil Sharma, Vipin Vageriya","doi":"10.1111/phn.13500","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence now encompasses technologies like machine learning, natural language processing, and robotics, allowing machines to undertake complex tasks traditionally done by humans. AI's application in healthcare has led to advancements in diagnostic tools, predictive analytics, and surgical precision.</p><p><strong>Aim: </strong>This comprehensive review aims to explore the transformative impact of AI across diverse healthcare domains, highlighting its applications, advancements, challenges, and contributions to enhancing patient care.</p><p><strong>Methodology: </strong>A comprehensive literature search was conducted across multiple databases, covering publications from 2014 to 2024. Keywords related to AI applications in healthcare were used to gather data, focusing on studies exploring AI's role in medical specialties.</p><p><strong>Results: </strong>AI has demonstrated substantial benefits across various fields of medicine. In cardiology, it aids in automated image interpretation, risk prediction, and the management of cardiovascular diseases. In oncology, AI enhances cancer detection, treatment planning, and personalized drug selection. Radiology benefits from improved image analysis and diagnostic accuracy, while critical care sees advancements in patient triage and resource optimization. AI's integration into pediatrics, surgery, public health, neurology, pathology, and mental health has similarly shown significant improvements in diagnostic precision, personalized treatment, and overall patient care. The implementation of AI in low-resource settings has been particularly impactful, enhancing access to advanced diagnostic tools and treatments.</p><p><strong>Conclusion: </strong>AI is rapidly changing the healthcare industry by greatly increasing the accuracy of diagnoses, streamlining treatment plans, and improving patient outcomes across a variety of medical specializations. This review underscores AI's transformative potential, from early disease detection to personalized treatment plans, and its ability to augment healthcare delivery, particularly in resource-limited settings.</p>","PeriodicalId":54533,"journal":{"name":"Public Health Nursing","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Health Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/phn.13500","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Artificial intelligence now encompasses technologies like machine learning, natural language processing, and robotics, allowing machines to undertake complex tasks traditionally done by humans. AI's application in healthcare has led to advancements in diagnostic tools, predictive analytics, and surgical precision.
Aim: This comprehensive review aims to explore the transformative impact of AI across diverse healthcare domains, highlighting its applications, advancements, challenges, and contributions to enhancing patient care.
Methodology: A comprehensive literature search was conducted across multiple databases, covering publications from 2014 to 2024. Keywords related to AI applications in healthcare were used to gather data, focusing on studies exploring AI's role in medical specialties.
Results: AI has demonstrated substantial benefits across various fields of medicine. In cardiology, it aids in automated image interpretation, risk prediction, and the management of cardiovascular diseases. In oncology, AI enhances cancer detection, treatment planning, and personalized drug selection. Radiology benefits from improved image analysis and diagnostic accuracy, while critical care sees advancements in patient triage and resource optimization. AI's integration into pediatrics, surgery, public health, neurology, pathology, and mental health has similarly shown significant improvements in diagnostic precision, personalized treatment, and overall patient care. The implementation of AI in low-resource settings has been particularly impactful, enhancing access to advanced diagnostic tools and treatments.
Conclusion: AI is rapidly changing the healthcare industry by greatly increasing the accuracy of diagnoses, streamlining treatment plans, and improving patient outcomes across a variety of medical specializations. This review underscores AI's transformative potential, from early disease detection to personalized treatment plans, and its ability to augment healthcare delivery, particularly in resource-limited settings.
期刊介绍：
Public Health Nursing publishes empirical research reports, program evaluations, and case reports focused on populations at risk across the lifespan. The journal also prints articles related to developments in practice, education of public health nurses, theory development, methodological innovations, legal, ethical, and public policy issues in public health, and the history of public health nursing throughout the world. While the primary readership of the Journal is North American, the journal is expanding its mission to address global public health concerns of interest to nurses.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
