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Imaging IT

Image: Researchers have designed an AI algorithm that uses CT scan images to process medical images and extract biological and clinical information (Photo courtesy of iStock).

Researchers Develop AI Algorithm to Predict Immunotherapy Response

A team of French researchers have designed an algorithm and developed it to analyze Computed Tomography (CT) scan images, establishing for the first time that artificial intelligence (AI) can process medical images to extract biological and clinical information. The researchers have created a so-called radiomic signature, which defines the level of lymphocyte infiltration of a tumor and provides a predictive score for the efficacy of immunotherapy in the patient. More...
12 Sep 2018
Image: Researchers are working to develop the application of AI in medical imaging diagnostics (Photo courtesy of Digital Health).

Fujifilm and IU School of Medicine to Study AI in Diagnostic Imaging

Fujifilm Corporation has entered into a joint research agreement with Indiana University School of Medicine to develop the application of artificial intelligence (AI) in medical imaging diagnostic support systems. More...
12 Sep 2018
Radcal
Image: The Virtual Brain Segmenter could increase the efficiency of brain scan analysis (Photo courtesy of Dominique Duncan).

VR Tool Increases Efficiency of Brain Scan Analysis

Researchers at the Mark and Mary Stevens Neuroimaging and Informatics Institute at the Keck School of Medicine of University of Southern California have designed a virtual reality (VR) tool for correcting errors in brain scan data. The tool named Virtual Brain Segmenter (VBS) transforms a tedious step in the scientific process into an immersive experience and significantly increases the efficiency of brain scan analysis. More...
06 Sep 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...
05 Apr 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...
05 Apr 2018
Italray
Image: syngo Dynamics facilitates CVIS access across the healthcare continuum (Photo courtesy of Siemens Healthineers).

Next-Generation CVIS Upgrades Communicability and Security

An updated cardiovascular imaging and Information system (CVIS) enhances communication and efficiency across the care continuum. More...
20 Mar 2018
Image: The scatterplot shows the machine learning model score compared to a random number in the independent test set (Photo courtesy of RSNA).

Researchers Train Model to Identify Breast Lesions

Researchers have trained a machine-learning tool to identify high-risk, biopsy-diagnosed breast cancer lesions that are unlikely to become cancerous, and do not require immediate surgery. More...
24 Oct 2017

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