Health Needs and Priorities of an Underserved Karenni Refugee Community: A Community Needs Assessment [0.03%]
一项社区需求评估：一个无服务克伦族难民社区的需求和优先事项
Ana D Sucaldito,Htay Meh,Scott D Rhodes et al.
Ana D Sucaldito et al.
Background: Southeast Asian refugee communities are frequently underserved by social and medical systems and experience profound health and health care inequities. The purpose of this study was to detail the health needs,...
Sarcoidosis Mortality in North Carolina: Role of Region, Race, and Other Sociodemographic Variables [0.03%]
北卡罗来纳州的 sarcoidosis 死亡率：地区、种族及其他社会人口学因素的作用
David Wambui,Gregory Kearney,Kevin O&#x;Brien et al.
David Wambui et al.
Background: There is regional variability in sarcoidosis mortality across the United States. North Carolina ranks highly in sarcoidosis-related mortality, especially among African Americans (AA). We sought to determine an...
A Health Care Clinical Data Platform for Rapid Deployment of Artificial Intelligence and Machine Learning Algorithms for Cancer Care and Oncology Clinical Trials [0.03%]
用于癌症护理和肿瘤临床试验的人工智能和机器学习算法的快速部署的医疗保健临床数据平台
Soma Sengupta,Rohan Rao,Zachary Kaufman et al.
Soma Sengupta et al.
The xCures platform aggregates, organizes, structures, and normalizes clinical EMR data across care sites, utilizing advanced technologies for near real-time access. The platform generates data in a format to support clinical care, accelera...
A Compass for North Carolina Health Care Workers Navigating the Adoption of Artificial Intelligence [0.03%]
北卡罗来纳州医疗工作者应对人工智能应用的指南
Yvonne Mosley,Miriam Tardif-Douglin,LaPonda Edmondson
Yvonne Mosley
This article underscores the economic benefits of AI, the importance of collaborative innovation, and the need for workforce development to prepare health care professionals for an AI-enhanced future. We include guidance for strategic and e...
Comments on Contemporary Uses of Machine Learning for Electronic Health Records [0.03%]
论当前电子健康记录中机器学习的用途
Jordan Bryan,Didong Li
Jordan Bryan
Various decisions concerning the management, display, and diagnostic use of electronic health records (EHR) data can be automated using machine learning (ML). We describe how ML is currently applied to EHR data and how it may be applied in ...
Sean Harrison,Melissa Leigh,Daniel Hallenbeck
Sean Harrison
This article explores the current and potential applications of AI in care management and health care administration through the experience of Acentra Health. By discussing various AI use cases, this paper highlights how AI can augment the ...
AI and Social Determinants of Health in Health Care: A Personal Perspective [0.03%]
人工智能与医疗健康的社会决定因素：个人视角
Ashok Krishnamurthy,Jessica K Zègre-Hemsey,Rebecca R Kitzmiller et al.
Ashok Krishnamurthy et al.
As a biomedical data scientist, when I think of the future of artificial intelligence in health care, the potential fills me with both excitement and caution. A promising area of innovation, AI can be used to assess the impact of social det...
"Don't Panic" - Stephen Aylward, PhD, on AI in Medical Imaging [0.03%]
“不要惊慌”——Stephen Aylward博士谈医学影像领域的AI技术
Sean Sylvia,Stephen Aylward
Sean Sylvia
Toward an "Equitable" Assimilation of Artificial Intelligence and Machine Learning into Our Health Care System [0.03%]
朝向使人工智能和机器学习技术以“公平”的方式融入医疗体系的发展之路
Ritu Agarwal,Guodong Gao
Ritu Agarwal
Enthusiasm about the promise of artificial intelligence and machine learning in health care must be accompanied by oversight and remediation of any potential adverse effects on health equity goals that these technologies may create. We desc...