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AI

Image: A new artificial-intelligence-based approach to image reconstruction – called AUTOMAP – yields higher quality images from less data, reducing radiation doses for CT and PET and shortening scan times for MRI. Shown here are MR images reconstructed from the same data with conventional approaches (left) and AUTOMAP (right) (Photo courtesy of Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital).

New AI Technique Dramatically Improves Quality of Medical Imaging

Researchers have developed a new technique based on artificial intelligence (AI) and machine learning that enables radiologists to acquire higher quality images without having to collect additional data at the cost of increased radiation dose for computed tomography (CT) and positron emission tomography (PET) or uncomfortably long scan times for magnetic resonance imaging (MRI). More...
05 Apr 2018
Image: Canon Medical Systems has initiated collaborative research on the application of AI-based technology in magnetic resonance imaging (Photo courtesy of iStock).

Canon Medical Systems Initiates Collaborative Research On AI in MR Imaging

Canon Medical Systems Corporation, along with Kumamoto University and the University of Bordeaux, has initiated collaborative research on the application of Deep Learning Reconstruction (DLR), an Artificial Intelligence (AI)-based technology in magnetic resonance (MR) imaging. More...
05 Apr 2018
Image: Cognitive neuroscientists are using the newly developed AI networks to enhance the understanding of the human brain (Photo courtesy of TechSource).

Dissecting AI to Better Understand the Human Brain

At the 25th annual meeting of the Cognitive Neuroscience Society (CNS), researchers presented their work in which cognitive neuroscientists are increasingly using emerging artificial networks to enhance their understanding of one of the most elusive intelligence systems, the human brain. Among the work presented at the symposium at the CNS annual meeting held in Boston from March 24-27, 2018, was “Human and machine cognition: The deep learning challenge” by Aude Oliva of MIT. In Oliva’s work, neuroscientists are learning much about the role of contextual clues in human image recognition. By using “artificial neurons” – essentially lines of code, software – with neural network models, they can parse out the various elements that go into recognizing a specific place or object. More...
04 Apr 2018
Image: MRI images reconstructed from the same data with conventional approaches (L) and AUTOMAP (R) (Photo courtesy of MGH).

AI Technique Dramatically Improves Medical Imaging Quality

A new technique based on artificial intelligence (AI) and machine learning could enable clinicians to acquire high-quality images from limited data. More...
02 Apr 2018
Image: The PeriWatch Vigilance is designed as a new fetal and maternal early warning platform (Photo courtesy of PeriGen).

AI-Powered Early Warning Solution Facilitates Timely Intervention

PeriGen, a provider of perinatal early warning systems, delivered a sneak peek of PeriWatch Vigilance, its new fetal and maternal early warning platform, at the 2018 HIMSS Conference & Exhibition (HIMSS18). More...
12 Mar 2018
Image: The HealthSuite Insights platform is designed to give data scientists, software developers, clinicians and healthcare providers access to advanced analytic capabilities to curate and analyze healthcare data, and offers them tools and technologies to build, maintain, deploy and scale AI-based solutions (Photo courtesy of Philips Healthcare).

Philips Launches Artificial Intelligence Platform for Healthcare

Royal Philips has launched HealthSuite Insights, including the Insights Marketplace, to support the advancing adoption of analytics and artificial intelligence (AI) in key healthcare domains. HealthSuite Insights, which made its debut at the 2018 HIMSS Conference & Exhibition (HIMSS18), gives data scientists, software developers, clinicians and healthcare providers access to advanced analytic capabilities to curate and analyze healthcare data, and offers them tools and technologies to build, maintain, deploy and scale AI-based solutions. Insights Marketplace will provide the healthcare industry's first ecosystem where curated AI assets from Philips and others are readily available for license. More...
12 Mar 2018
Image: New research suggests machine learning can enhance digital healthcare tools by aiding routine processes and helping physicians to assess patient risk (Photo courtesy of iStock).

Machine Learning Shows Promise for Supporting Medical Decisions

A number of studies presented at the 67th Annual Scientific Session of the American College of Cardiology demonstrated how machine learning can be used to accurately predict clinical outcomes in patients with known or potential heart problems. The findings of these studies indicate that machine learning can usher in a new era in digital health care tools capable of enhancing health care delivery by aiding routine processes and helping physicians to assess the patients’ risk. More...
01 Mar 2018


 The Artificial Intelligence channel of HospiMedica keeps the reader informed about the latest news in AI-based clinical decision making, Medical knowledge engineering, Intelligent medical information systems and additional related fields.
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