Artificial Intelligence

This channel includes news and technology innovations for artificial intelligence (AI) software, also referred to as deep learning, cognitive computing and machine learning. AI technology is being integrated in radiology for imaging appropriate use criteria (AUC), clinical decision support, predictive analytics and to assist radiologists with improved workflow.

 Recently the versatility of mixed and augmented reality products has come to the forefront of the news, with an Imperial led project at the Imperial College Healthcare NHS Trust. Doctors have been wearing the Microsoft Hololens headsets whilst working on the front lines of the COVID pandemic, to aid them in their care for their patients. IDTechEx have previously researched this market area in its report “Augmented, Mixed and Virtual Reality 2020-2030: Forecasts, Markets and Technologies”, which predicts th

Doctors wearing the Hololens Device. Source: Imperial.ac.uk

News | Artificial Intelligence | May 22, 2020
May 22, 2020 — Recently the versatility of mixed and augmented reality products has come to the forefront of the news,...
Hologic, Inc. announced that Unifi EQUIP, an automated solution that facilitates compliance with the FDA’s Enhancing Quality Using the Inspection Program (EQUIP) guidance, was recognized as "Best Overall MedTech Solution" in the 2020 MedTech Breakthrough Awards program.
News | Analytics Software | May 21, 2020
May 21, 2020 — Hologic, Inc. announced that Unifi EQUIP, an automated solution that facilitates compliance with the FDA...
In response to the significant healthcare delivery changes brought on by COVID-19, Varian has launched new capabilities for its Noona software application, a powerful tool designed to engage cancer patients in their care for continuous reporting and symptom monitoring.
News | Radiation Oncology | May 21, 2020
May 21, 2020 — In response to the significant healthcare delivery changes brought on by COVID-19, Varian has launched...
NucleusHealth, a provider of cloud-based medical image management technology and teleradiology services, announced today that it has received Conformité Européene (CE) Mark approval for Nucleus.io.
News | Teleradiology | May 21, 2020
May 21, 2020 — NucleusHealth, a provider of cloud-based medical image management technology and teleradiology services...
Extends access of AI software that supports chest imaging, including CT and X-ray, to U.S. radiologists at over 7,000 healthcare facilities
News | Coronavirus (COVID-19) | May 21, 2020
May 21, 2020 — RADLogics announced that its AI-powered medical imaging applications designed to assist in the detection...
Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-

Figure 1: Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-CoV-2. The CNN model identified abnormal features in the right lower lobe (white color), whereas the two radiologists labeled this CT as negative. (b) A 52-year-old female who had a history of exposure to SARS-CoV-2 and presented with fever and productive cough. Bilateral peripheral ground-glass opacities (arrows) were labeled by the radiologists, and the CNN model predicted positivity based on features in matching areas. (c) A 72-year-old female with exposure history to the animal market in Wuhan presented with fever and productive cough. The segmented CT image shows ground-glass opacity in the anterior aspect of the right lung (arrow), whereas the CNN model labeled this CT as negative. (d) A 59-year-old female with cough and exposure history. The segmented CT image shows no evidence of pneumonia, and the CNN model also labeled this CT as negative.  

News | Coronavirus (COVID-19) | May 19, 2020
May 19, 2020 — Mount Sinai researchers are the first in the country to use artificial intelligence (AI) combined with...
World’s largest deployment of a radiology-based AI diagnostic solution for COVID-19 using AI-based chest X-ray technology
News | Coronavirus (COVID-19) | May 18, 2020
May 18, 2020 — Behold.ai announced its partnership with Apollo Radiology International, part of the Apollo Hospitals...
Facilitates timely patient workup to allow for activation of COVID-19 related protocols
News | Coronavirus (COVID-19) | May 08, 2020
May 8, 2020 — Aidoc announced that the U.S. Food and Drug Administration (FDA) has allowed the use of their cleared AI...
These solutions, the Lung Density Analysis II (LDA-II) workflow for Intuition and the Emergency Lung AI Suite, provide two deployment options for rapid access to lung segmentation and quantification tools that can be applied to a wide range of lung illnesses and have been optimized to adapt to the latest disease presentation states
News | Artificial Intelligence | May 07, 2020
May 7, 2020 — As COVID-19 makes its way across the globe, our customers are urgently connecting with us to share cases...
A complex multicompartmental cerebral hemorrhage on a single axial CT image displayed using the annotation tool in a single portal window. Hemorrhage labels (left column) relevant to the image display on the bottom of the image once selected. ASNR = American Society of Neuroradiology RSNA = Radiological Society of North America.

A complex multicompartmental cerebral hemorrhage on a single axial CT image displayed using the annotation tool in a single portal window. Hemorrhage labels (left column) relevant to the image display on the bottom of the image once selected. ASNR = American Society of Neuroradiology RSNA = Radiological Society of North America. Image courtesy of RSNA

News | Artificial Intelligence | April 30, 2020
April 30, 2020 — An unprecedented collaboration among two medical societies and over 60 volunteer neuroradiologists has...
Artificial intelligence can categorize cancer risk of lung nodules
News | Artificial Intelligence | April 27, 2020
April 27, 2020 — Computed tomography (CT) scans for people at risk for lung cancer lead to earlier diagnoses and...
 Siemens Healthineers has received clearance from the Food and Drug Administration (FDA) for its AIDAN artificial intelligence technologies on the Biograph family of positron emission tomography/computed tomography (PET/CT) systems

 Siemens Healthineers received clearance from the FDA for its AIDAN artificial intelligence technologies on the Biograph family of positron emission tomography/computed tomography (PET/CT) systems.

News | Artificial Intelligence | April 22, 2020
April 22, 2020 — Siemens Healthineers has received clearance from the Food and Drug Administration (FDA) for its AIDAN...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 RADLogics announced new worldwide deployments and installations of the company’s AI-powered solution to support chest computed tomography (CT) imaging for COVID-19 (Coronavirus) patients.
News | Coronavirus (COVID-19) | April 21, 2020
April 21, 2020 — RADLogics announced new worldwide deployments and installations of the company’s AI-powered solution...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 Ambient clinical intelligence solution helps clinicians reduce administrative burden, increase patient throughput, and document care from anywhere
News | Teleradiology | April 20, 2020
April 20, 2020 — Nuance Communications, Inc. announced the Nuance Dragon Ambient eXperience (DAX) solution for...
Advanced technologies such as AI, blockchain and continuous authentication to transform the connected era in 2030
News | Cybersecurity | April 15, 2020
April 15, 2020 — Frost & Sullivan’s recent analysis, The Future of Privacy and Cybersecurity, Forecast to 2030,...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Artificial Intelligence | April 15, 2020
April 15, 2020 — behold.ai has been issued with a CE Mark Class lla certification in the U..K and EU for its AI-based...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 U.S. Army Spc. Jonathon Hyde and Spc. Casymn Harrison from the 1434th Engineer Company, Grayling, Mich., Michigan National Guard, prepare patient rooms at TCF Regional Care Center in Detroit in advance of receiving COVID-19 patients, April 9, 2020 #COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

U.S. Army Spc. Jonathon Hyde and Spc. Casymn Harrison from the 1434th Engineer Company, Grayling, Mich., Michigan National Guard, prepare patient rooms at TCF Regional Care Center in Detroit in advance of receiving COVID-19 patients, April 9, 2020. The TCF Center in Detroit has been converted into a 970-bed alternative care facility for COVID-19 patients by the Federal Emergency Management Agency, in partnership with the U.S. Army Corps of Engineers and Michigan National Guard. (Photo courtesy of U.S. Air National Guard photo by Master Sgt. Scott Thompson)

Feature | Coronavirus (COVID-19) | April 15, 2020 | By Melinda Taschetta-Millane and Dave Fornell
In an effort to keep the imaging field updated on the latest information being released on coronavirus (COVID-19), the...
Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Sponsored Content | Case Study | Artificial Intelligence | April 09, 2020
As the largest independent imaging group in Michigan with 10 locations across the state, Regional Medical Imaging (RMI...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Coronavirus (COVID-19) | April 09, 2020
April 9, 2020 — Care Mentor AI is developing an artificial intelligence (AI) system that will accelerate the analysis...
The agreement is intended to integrate Qure.ai’s proprietary technology for chest x-ray screening and head CT triage in the Nanox.Cloud to improve imaging solutions and increase patient access to medical imaging world-wide
News | Artificial Intelligence | April 07, 2020
April 7, 2020 — -NANO-X IMAGING LTD (Nanox), an innovative medical imaging company, announces its collaboration with ...