A research team at Universitat Autònoma de Barcelona (UAB), in collaboration with the Hospital de Mataró, developed a new machine learning-based model that predicts the risk of mortality of intensive care unit patients according to their characteristics. The research was published in the latest edition of the journal Artificial Intelligence in Medicine, with a special mention as a…
The Netherlands Cancer Institute, University of Amsterdam (UvA), and Elekta will collaborate on the development of new AI strategies for the further improvement of precision radiotherapy. This concerns the personalization of treatment by improving the quality of imaging used during treatment, predicting and accounting for changes in the patient’s anatomy over time, and automatically adapting…
A researcher at the Technical University of Denmark (DTU) has developed a mathematical model for use in automated image analysis of tissue samples. The model provides the possibility for better and more similar cancer prognosis and treatment.
At a virtual European event, Fujifilm Healthcare Europe presented a complete and integrated portfolio of diagnostic products and services, including CT, MRI, X-ray, AI, PACS, endoscopy and ultrasound systems. This launch follows the completion of Fujifilm's acquisition and takeover of Hitachi's Diagnostic Imaging-related business on 31 March 2021 for 179 billion yen (€1.3 billion).
The Covid-19 pandemic continues to impact people’s health across the world. This goes beyond the disease itself, as healthcare systems adapt how they provide services. Routine screening has been severely affected with screening programmes reduced or paused.
Artificial intelligence (AI) could match the impact of PACS on radiology. Covid-19 stimulated the development and testing of AI diagnostic-aiding tools in radiology, an unintended consequence of the pandemic. More image data sets have been created to train AI software – an unexpected benefit for radiology research.
Cancer care and the treatment clinicians can offer patients is being increasingly enhanced by Artificial Intelligence (AI). The technology has a role in diagnosis, with algorithms trained to design and deliver patient care, can match patients to clinical trials they may benefit from, and even help predict outcomes and those at greatest risk.
An international team of scientists led by EPFL has developed a system that combines information from the brain’s connectome – the “wiring” between neurons – and machine learning to assess and predict the outcome of stroke victims. When blood flow to the brain is somehow reduced or restricted, a person can suffer what we know as a stroke (from “ischemic stroke” in medical jargon).…
Pioneering technology developed by University College London (UCL) and Africa Health Research Institute (AHRI) researchers could transform the ability to accurately interpret HIV test results, particularly in low- and middle-income countries. Academics from the London Centre for Nanotechnology at UCL and AHRI used deep learning (artificial intelligence/AI) algorithms to improve health workers’…
Experts at University College London (UCL) and spinout company Odin Vision working with clinicians at UCLH have used artificial intelligence (AI) to help detect early signs of oesophageal cancer. The first procedure in the world using the AI technology was performed at University College Hospital by UCLH consultant gastroenterologist Dr Rehan Haidry. The system, called CADU, uses AI to support…
Artificial Intelligence (AI) holds great promise for improving the delivery of healthcare and medicine worldwide, but only if ethics and human rights are put at the heart of its design, deployment, and use, according to new WHO guidance.
Technologies based on artificial intelligence (AI) are considered the epitome of progress. However, the data AI algorithms use to draw their conclusions is outdated. It ignores the existence of biological sex and socio-cultural gender and their effects on individual health and disease states. German experts discussed the gender problem in healthcare AI at virtual.MEDICA 2020.
In noisy environments, it is difficult for hearing aid or hearing implant users to understand their conversational partner because current audio processors still have difficulty focusing on specific sound sources. In a feasibility study, researchers from the Hearing Research Laboratory at the University of Bern and the Inselspital are now suggesting that artificial intelligence (AI) could solve…
The contribution of Artificial intelligence (AI) has great potential in breast imaging efficiency, Professor Linda Moy MD told attendees at the 2021 Society of Breast Imaging/American College of Radiology (SBI/ACR) Breast Imaging Symposium this April. AI models for breast imaging have focused mainly on the diagnostic classification and detection of breast cancer.
When patients are admitted to a hospital emergency room (ER) it is immediately vital to determine whether s/he has Covid-19. However, with a regular PCR test a result can take up to a few hours. Thus, initially, the patient must be isolated. During the height of the corona pandemic last year, researcher Ruben Deneer from Eindhoven University of Technology (TU/e) and clinical chemist Arjen-Kars…
Canon Medical announced the commercial launch of the Aplio i-series / Prism Edition, a complete redesign of its premium ultrasound series. In addition, Aplio a-series, Canon Medical’s routine-to-advanced imaging range has also received a significant refresh.
When viruses infect cells, changes in the cell nucleus occur, and these can be observed through fluorescence microscopy. Using fluoresence images from live cells, researchers at the University of Zurich have trained an artificial neural network to reliably recognize cells that are infected by adenoviruses or herpes viruses. The procedure also identifies severe acute infections at an early stage.
Dr. Hayder Amin and Dr. Caghan Kizil from the DZNE’s Dresden site aim to speed up developing drugs against brain diseases through cutting-edge technology. To this end, they are generating an innovative technology platform, termed “i3D-Markers”, based on high-density microelectrode arrays and 3-dimensional networks of human neurons. Compounds to be tested will be dripped onto this setup, and…
New artificial intelligence (AI) technology to scan for heightened blood vessel inflammation can calculate a person’s risk of death from Covid-19 and its variants.
University of Washington researchers have discovered that AI models—like humans—have a tendency to look for shortcuts. In the case of AI-assisted disease detection, these shortcuts could lead to diagnostic errors if deployed in clinical settings.
Three leading AI scale-ups - Aidence, ScreenPoint Medical and Thirona - have launched the informative video series “Opening the black box of AI in medical imaging”.
A new platform allows hospitals to deliver improved organisational and financial performance by deploying an Internet of Things (IoT) sensor network to collect data and using AI to analyse the gathered information in a HIPAA-compliant way.
Identifying new uses for approved therapeutic drugs continues to drive academics and clinicians to provide safe, affordable and rapid development of new treatment options for patients with common or rare diseases.
Communities benefit from sharing knowledge and experience among their members. Following a similar principle - called “swarm learning” - an international research team has trained artificial intelligence algorithms to detect blood cancer, lung diseases and Covid-19 in data stored in a decentralized fashion. This approach has advantage over conventional methods since it inherently provides…
Heart disease and cancer are the leading causes of death in the United States, and it’s increasingly understood that they share common risk factors, including tobacco use, diet, blood pressure, and obesity. Thus, a diagnostic tool that could screen for cardiovascular disease while a patient is already being screened for cancer has the potential to expedite a diagnosis, accelerate treatment, and…