dismiss

Clean Sweep Live Auction on Wed. May 1st. Click to view the full inventory

DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Pediatrics
SEARCH
当前地点:
>
> This Story


注册记数器 to rate this News Story
Forward Printable StoryPrint Comment
advertisement

 

advertisement

 

Artificial Intelligence Homepage

Aidoc announces $27 million in VC funding to advance AI in imaging Brings company's total funding to $40 million

Fredrik Palm ContextVision appoints new CEO

ACR engages in collaborations for AI development with launch of AI-LAB platform Allows radiologists to create algorithms of their own

New AI software identifies make and model of cardiac implants in seconds Speed up diagnosis and delivery of treatment for patients with faulty devices

Dicom Systems scores enterprise imaging contract with Radiology Partners Will integrate IT and clinical workflows of more than 850 provider facilities

Apple study suggests wearable technology may be useful in detecting atrial fibrillation May assist in stroke and hospitalization prevention

Nvidia unveils Clara AI platform at GPU Technology Conference Equipped with 13 state-of-the-art classification and segmentation algorithms

BSWH to install Glassbeam's CLEAN blueprint to leverage machine uptime Will include integrated CMMS software by EQ2

Beyond the hype: How practical AI is enhancing radiology Insights from Imad B. Nijim, chief information officer for MEDNAX Radiology Solutions

Machine learning reduces false positives for lung cancer in low-dose CT False positives occur at rate of 96 percent

A new study says patients need to
be educated more on the precise
use of AI in the scanning process

New study questions patient understanding on AI in radiology

John R. Fischer , Staff Reporter
A new study says patients vary in their understanding of the different roles that make up a radiology department, and are skeptical of and lack knowledge on the capabilities offered by artificial intelligence.

Conducted by Dutch researchers, the qualitative assessment argues that more education is necessary to help patients understand how AI is used in the scanning process, and where the roles of different staff members in radiology stand in relation to its use. Once attained, this knowledge will enable them to be better able to contribute input for determining best practices and use of AI and machine learning in these types of settings.

Story Continues Below Advertisement

Servicing GE Nuclear Medicine equipment with OEM trained engineers

We offer full service contracts, PM contracts, rapid response, time and material,camera relocation. Nuclear medicine equipment service provider since 1975. Click or call now for more information 800 96 NUMED



“Since patients' level of knowledge on both artificial intelligence and radiology is generally low, the combination generates mixed feelings among patients,” Dr. Marieke Haan, assistant professor in the department of Sociology at University of Groningen, told HCB News. “In all of the six domains we formed based on our findings, patients expressed concerns but also showed their beliefs in a promising future.”

The study refers to patients as “important but neglected” stakeholders who are “crucial” to determining the development and uses of AI systems for various clinical tasks in routine radiology practices.

Surveying 20 individual members from a group of 11 men and nine women at the department of radiology of the University Medical Center Groningen, the research team broke their responses down into six sections of information that sum up patient needs, concerns and viewpoints:

• Proof of technology: Patients desire scientific evidence to validate the use of an AI system in radiology, before it is actually used. When presented with findings that showed AI as equivalent in skill to humans, patients preferred to have a human perform their exam. Machines, however, were preferred when research showed computers to be superior.

• Procedural knowledge: Patients want to know how AI is exactly used, and want to receive incidental and unrequested findings in addition to those that are based on questions of the referring physicians. They are unclear about how AI affects scanning procedures and the delivery of findings, as well as unaware of who is involved in exams and how roles such as radiologist, technician and referring physician differ from one another in relation to the use of AI.

• Competence: Patients are skeptical of AI and believe using it only could lead to restricted views with wrong diagnoses. They are unsure about the skills of computers, and believe they should be used as secondary sources to validate the conclusions of radiologists.
  Pages: 1 - 2 >>

Artificial Intelligence Homepage


You Must Be Logged In To Post A Comment

做广告
提升您的品牌知名度
拍卖+私人销售
获得最好的价格
买设备/配件
找到最低价格
每日新闻
阅读最新信息
目录
浏览所有的DOTmed用户
DOTmed上的伦理
查看我们的伦理计划
金子分开供营商节目
接收PH要求
金子服务经销商节目
接收请求
提供保健服务者
查看所有的HCP(简称医疗保健提供商)的工具
工作/训练
查找/申请工作
Parts Hunter +EasyPay
获取配件报价
最近证明
查看最近通过认证的用户
最近额定
查看最近通过认证的用户
出租中央
租用设备优惠
卖设备/配件
得到最划算
服务技术员论坛
查找帮助和建议
简单的征求建议书
获取设备报价
真正商业展览
查找对设备的服务
对这个站点的通入和用途是受期限和条件我们支配 法律公告 & 保密性通知
物产和业主对 DOTmed.com,公司 Copyright ©2001-2019 DOTmed.com, Inc.
版权所有