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Industry News

Image: A new algorithm uses signatures from MRI, genetics and clinical data to predict susceptibility to Alzheimer’s disease (Photo courtesy of iStock).

AI Algorithm Uses Key Signatures to Predict Onset of AD

A team of researchers has designed an artificial intelligence (AI) algorithm that learns signatures from magnetic resonance imaging (MRI), genetics, and clinical data to accurately predict cognitive decline leading to Alzheimer’s disease. The algorithm can help predict whether an individual’s cognitive faculties are likely to deteriorate towards Alzheimer’s in the next five years. More...
15 Oct 2018
Image: The breast cancer screening software is intended to detect cancer at an earlier stage, as well as reduce radiation dose and the number of invasive biopsies (Photo courtesy of iStock).

Breast Cancer Screening Machine Learning Software Receives CE Mark

A new deep learning-based breast cancer screening software has received the CE mark and will be launched within the UK’s National Health Service (NHS) and European healthcare systems. The software has been developed by Kheiron Medical Technologies, a start-up that combines novel deep learning methods, data science, and radiology expertise to enable diagnostics designed to detect cancers and improve patient outcomes. More...
15 Oct 2018
Image: Researchers used AI and MRI to identify learning difficulties in children (Photo courtesy of iStock).

Scientists Use Machine Learning and MRI Scans to Predict Learning Difficulties

A team of scientists from the Medical Research Council (MRC) Cognition and Brain Sciences Unit at the University of Cambridge used machine learning - a type of artificial intelligence - with data from hundreds of children who struggle at school to identify clusters of learning difficulties, which did not match their previous diagnosis. According to the researchers, this reinforces the need for children to receive detailed assessments of their cognitive skills to identify the best type of support. More...
11 Oct 2018
Image: The Mammomat Revelation mammography system (Photo courtesy of Siemens Healthineers).

Utilization of X-Ray Mammography Systems Expected to Increase

Over the last 20 years, hospitals and imaging centers in the developed economies have adopted X-ray mammography systems for the screening and diagnosis of breast cancer. This has resulted in a significant reduction in mortality and encouraged emerging countries to make investments in population-base, organized screening. These significant investments in mammography technology have paved the way for radiation safety, patient comfort and 3D imaging that enables precise tumor detection. More...
10 Oct 2018
Image: The vScan handheld ultrasound device (Photo courtesy of GE Healthcare).

Compact Devices Emerge As Segment of Ultrasound Market

The global ultrasound devices market was valued at USD 6.5 billion in 2017 and is projected to grow at a CAGR of 5.6% from 2018 to 2026 to reach USD 10.6 billion by 2026, as a surge in the incidence of disorders such as cardiovascular diseases, respiratory and abdominal disorders is likely to boost the demand for ultrasound devices. More...
09 Oct 2018
Image: A study carried out by neuroscientists and AI researchers provides insight into the way the human brain connects individual episodic memories to solve problems (Photo courtesy of Shutterstock).

AI and fMRI Show How Brain Connects Memories to Solve Problems

A team of German neuroscientists and Artificial Intelligence (AI) researchers have published results from their study that provided insights into the way the human brain connects individual episodic memories, or memories of specific events, to solve problems. More...
02 Oct 2018
Image: An AI tool analyzes a slice of cancerous tissue to create a map that tells apart two lung cancer types, with squamous cell carcinoma in red, lung squamous cell carcinoma in blue, and normal lung tissue in gray (Photo courtesy of Cision).

AI Tool Identifies Cancer Type and Changes in Lung Tumor

Researchers from the NYU School of Medicine have developed a new computer program that can analyze the images of patients' lung tumors, specify cancer types, and even identify altered genes driving abnormal cell growth. In their study, the researchers found that the artificial intelligence (AI), or "machine learning," program could distinguish -- with 97% accuracy -- between adenocarcinoma and squamous cell carcinoma, two lung cancer types that experienced pathologists at times struggle to parse without confirmatory tests. Additionally, the study found that the AI was also able to determine from analyzing the images whether the abnormal versions of six genes linked to lung cancer – including EGFR, KRAS and TP53 – were present in cells, with an accuracy ranging from 73% to 86%, depending upon the gene. More...
01 Oct 2018
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