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 Mobile Imaging
SEARCH
当前地点:
>
> This Story


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

 

 

Artificial Intelligence Homepage

Dr. Brian Avants Invicro hires senior director of machine learning

MaxQ-AI seeks $8 million public IPO listing on Nasdaq Will help FDA regulatory processes for Accipio software products

Siemens and NuVasive collab to enhance spinal surgery Combines NuVasive's Pulse system with Siemens Cios Spin

FDA clears Aidoc AI solution for triaging head CT scans Flags acute intracranial hemorrhage cases by focusing on abnormal regions

CureMetrix teams with University of Florida on CAD development Developing software for 3D tomosynthesis

Despite added AI costs, there are likely benefits for radiologists More questions than answers when it comes to the business side of AI in imaging

Watson for Oncology gave unsafe recommendations: report Highlights the importance of training in machine learning

Viz.ai to extend LVO AI-based platform beyond stroke Using $21 million from Series A funding to do so

Could AI and 3D printing be the future of OB/GYN ultrasound? Few specialities are equally poised to embrace these cutting edge tools

Digital Surgery launches first real-time AI surgical system for OR New approach may help increase qualified surgeons, global access to care

AI in medical imaging to top $2 billion by 2023: Signify Research

Thomas Dworetzky , Contributing Reporter
Through software for automated detection, quantification, decision support and diagnosis, machine learning is making major inroads into medical imaging. The way things are going, the market is likely to top $2 billion by 2023, according to a new Signify Research market report.

Despite years of seemingly relentless hype, it's “becoming increasingly clear that AI will transform the diagnostic imaging industry, both in terms of enhanced productivity, increased diagnostic accuracy, more personalized treatment planning, and ultimately, improved clinical outcomes,” noted the report.

Story Continues Below Advertisement

Source-Ray, Inc. - Innovations In Portable X-Ray

SRI is a leading Developer, Manufacturer & Supplier of Innovative Portable Imaging Equipment. We offer Lightweight, Agile, Easy to Maneuver Portable X-Ray Systems ideal for maneuvering in tight spaces. Call us at 631-244-8200



With its future key role in letting radiologists handle the ever-growing volume of diagnostic imaging data, the issue of investing in the “right” software will remain a challenge.

“Many of the AI-based solutions for medical imaging that are coming to market are positioned as workflow productivity tools, but there is often a lack of clinical validation to show how much time these tools actually save and their real impact on how radiologists work,” Signify analyst and study author Simon Harris told HCB News, noting that, “similarly, there are few large-scale clinical studies on the accuracy of quantitative tools that provide automatic measurements of image features, such as the long and short measurements of lung nodules, and the variability of the results obtained from tools from different vendors.”

Harris advised healthcare providers interested in making an AI investment “to look for vendors who have invested in clinical studies and are able to provide robust clinical evidence to back up their marketing claims.”

The study noted that the development pace “is faster than ever before,” and is leading to a surge in products from more vendors.

"The interest and enthusiasm for AI in the radiologist community has notably increased over the last 12 to 18 months, and the discussion has moved on from AI as a threat, to how AI will augment radiologists,” suggested Harris, adding, “At the same time, there are emerging clinical applications where the use of AI has been shown to both improve clinical outcomes and deliver a return on investment for healthcare providers. Examples include software to detect and diagnose stroke, and analysis tools to measure blood flow in noninvasive coronary exams.”

Still in its innovator and early adopter phase, AI for medical imaging faces several challenges, including a regulatory process that has been slow to approve products and a lack of large-scale studies to illustrate that deep learning algorithms works in real-world clinical settings.
  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 ©2001-2018 DOTmed.com, Inc.
版权所有