We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Register Free
Advertise with Us
Latest Issue
Latest Issue
IBA-Radcal

Download Mobile App




Artificial Intelligence

Image: Google DeepMind is exploring new frontiers in medical diagnostics (Photo courtesy of Google).

DeepMind Masters Retinal Disease Detection

Artificial intelligence (AI) can accurately detect 53 kinds of sight-threatening retinopathy at least as effectively as experts, claims a new study. More...
27 Aug 2018

Intel and Philips Partner to Speed Up Imaging Analysis Using AI

Intel Corporation and Royal Philips have tested two healthcare use cases for deep learning inference models: one on X-rays of bones for bone-age-prediction modeling and the other on CT scans of lungs for lung segmentation. In these tests, which were conducted using Intel Xeon Scalable processors and the OpenVINO toolkit, the researchers achieved a speed improvement of 188 times for the bone-age-prediction model and 38 times for the lung-segmentation model over the baseline measurements. These tests show that healthcare organizations can implement artificial intelligence (AI) workloads without expensive hardware investments. More...
22 Aug 2018
Image: NYU School of Medicine’s Department of Radiology chair Michael Recht, M.D, Daniel Sodickson, M.D, Ph.D. vice chair for research and director of the Center for Advanced Imaging Innovation and Research and Yvonne Lui, M.D, director of artificial intelligence, watch an MRI exam take place with a technician at NYU Langone Health in August 2018 (Photo courtesy of the NYU School of Medicine).

Facebook Collaborates with NYU School of Medicine to Make MRI Scans Faster

Facebook, Inc. and the NYU School of Medicine’s Department of Radiology have announced a new collaborative research project named fastMRI that will investigate the use of artificial intelligence (AI) for making magnetic resonance imaging (MRI) scans up to 10 times faster. The project aims at making MRI technology available to more people, thereby expanding access to the key diagnostic tool. More...
22 Aug 2018
Image: Researchers aim to improve the quality of life for patients suffering from glioblastoma with a machine-learning model that makes chemotherapy and radiotherapy dosing regimens less toxic but still as effective as human-designed regimens (Photo courtesy of MIT).

Researchers Develop AI Model to Make Cancer Treatment Less Toxic

Researchers from the Massachusetts Institute of Technology have developed an artificial intelligence model that “learns” from patient data to make cancer-dosing regimens less toxic but still effective. More...
20 Aug 2018

Guerbet Partners with Imalogix on Dose Optimization with AI

Guerbet LLC USA, the US affiliate of the the Guerbet Group, which specializes in contrast product and solutions for medical imaging, has entered into a commercial partnership with Imalogix, a provider of artificial intelligence (AI) process and workflow solutions. More...
20 Aug 2018
Image: Comparison of two example mammograms from DDSM and INbreast (Photo courtesy of ResearchGate).

Deep Learning-Based System Detects and Classifies Mammogram Masses

Researchers from the Kyung Hee University have developed a fully integrated computer-aided diagnosis (CAD) system that uses deep learning and a deep convolutional neural network (CNN) to detect, segment and classify masses from mammograms. In a new study published by the International Journal of Medical Informatics, the researchers have described the use of their regional deep learning model, You-Only-Look-Once (YOLO), to detect breast mass from entire mammograms. The researchers then went on to use a new deep network model based on a full resolution convolutional network (FrCN), to segment the mass lesions pixel-to-pixel. Finally, a deep CNN was used to recognize the mass and classify it as either benign or malignant. More...
16 Aug 2018
Image: MRI reconstruction example. (a) Input image with only 10% of spectrum samples retained and scaled by 1/p. (b) Reconstruction by a network trained with noisy target images similar to the input image. (c) Original, uncorrupted image (Photo courtesy of NVIDIA).

AI Software for Restoring Photos Could Find Use in Medical Imaging

Researchers have developed a deep learning-based approach that can fix photos originally taken in low light and are grainy or pixilated, and automatically remove the noise and artifacts by simply looking at examples of corrupted photos only. The approach can also be used to enhance MRI images, which could pave the way for a drastic improvement in medical imaging. More...
16 Aug 2018
Visit expo >
Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Antipsychotic TDM Assays
Saladax Antipsychotic Assays
Neonatal Ventilator Simulation Device
Disposable Infant Test Lung
Emergency Ventilator
Shangrila935

In Other News



 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.

HospiMedica

About Us
Advertising Info
Subscription
Client Login
Privacy Policy
Terms of Service
Cookie Policy
Journal Info
Contact Us

Channels

AI
Critical Care
Surgical Techniques
Patient Care
Health IT
Point of Care
Business
Events
Focus
Webinars

Features

Events Product Showcase LinkXpress Whitepapers archive Video Library

Partner Sites

HospiMedica ExpoMedImaging.netLabMedica.com Globetech.net

Archive:

COVID-19

2025
Medica 2024
Medica ARAB HEALTH 2023
Medica ARAB HEALTH 2022

 

MEDICA Arab Health 2021
Medica Arab Health COV 2020
ARAB HEALTH 2019
Medica
Copyright © 2000-2026 Globetech Media. All rights reserved.
MOBILE | FULL SITE