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

New 'roadmap' paves the way for AI innovations in radiology Aims to advance foundational AI research for imaging

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

New study questions patient understanding on AI in radiology Asserts that greater education and communication is required

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

The pulse of medical AI: An innovation prognosis

By Elad Walach and Dr. Yoni Goldwasser

The transformative impact of AI on healthcare has stopped being a point for debate. It's not a question of "if," but of "how," and "how fast."

The field of medical imaging is a prime example of one of the many healthcare subfields that will feel the effects of AI on their workflow in the near future. AI will bring immense gain at each stage in the imaging value chain, which will no doubt be followed by the challenge of adoption for hospitals and radiologists. AI-focused startups and multinationals alike are both seizing the opportunities presented by this growing area of innovation.
Story Continues Below Advertisement

Free Marketplace where Lenders Compete Get Pre-Approved for up to $500,000

Get financing today. We say YES more! Easy, Fast, Application. Pick the payment that best works for you. Tax Benefits + Leasing = Huge Savings! NEVER BE OBSOLETE. NO DOWN PAYMENT. FIXED MONTHLY PAYMENT. MRI, CT, Ultrasound, Digital X-ray, Dental Equipment


AI will bring value at various points in the healthcare value chain
The imaging value chain can be broken down into several stages, with AI contributing in each:

  • Scheduling, administration, patient management, and workflow optimization. Given the current inefficiencies utilizing imaging technologies, the complex interface between various providers and the changing regulatory environment regarding these applications, AI offers a much-needed way of optimizing patient management. Companies like HealthLevel are trying to help radiologists improve efficiencies by providing BI and clinical metrics. Other solutions from the HIS/RIS space will continue to come into play in the coming years.

  • Pre-scan (e.g., patient positioning): While choosing the correct protocols and ensuring proper patient positioning is ostensibly the responsibility of physicians and technicians, AI algorithms can help prevent errors, improper care, and other difficulties. Bay Labs and Butterly iQ, for instance, use AI to reduce operator dependence in ultrasounds.

  • In-scan: One study's results often lead to further studies, wasting resources and prolonging time to diagnosis and care. Through live image processing, AI algorithms could help predict the need to employ new protocols or conduct further studies.

  • Post-scan/interpretation: Here is where AI's potential to streamline workflows is particularly valuable. AI can help radiologists prioritize caseloads – reducing, in some settings, more than 90% of diagnosis time for time-sensitive cases. Some AI companies try to target a broad set of clinical use cases (e.g., Aidoc, Zebra Medical, etc.), while others offer deep specialty around specific solutions.

  • Predictive analytics/biomarkers – Companies like Quantib and IcoMetrix are trying to find new biomarkers for complex cases like Alzheimer's, helping radiologists spot patterns invisible to the naked eye.

  Pages: 1 - 2 - 3 >>

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