Robotic ‘coaches’ which help aid upper limb rehabilitation for stroke and brain injury survivors have been successfully trialled in Vienna, Austria as part of an international pilot study led by researchers from the UK’s National Robotarium.
Researchers introduced a benchmarking method to assess autonomous navigation in hospital robots, focusing on metrics like completion time and success rate.
Samueli Integrative Cancer Pioneering Institute at Davidoff Cancer Center in Beilinson, and startup company XOLTAR sign a multi-year agreement to jointly lead an innovative research project: an AI companion to support breast cancer patients and monitor side effects during oncological treatments.
In a recent study, published in the journal Heliyon, researchers from Yale School of Medicine found that an artificial intelligence (AI) model can accurately diagnose individuals with Marfan Syndrome based on a basic facial picture.
Researchers developed an automated microfluidic system for preparing sequencing libraries, making next-generation sequencing more accessible and efficient, especially for point-of-care diagnostics. The device offers comparable performance to manual methods, enhancing NGS usability in clinical settings.
According to a study published in Radiology, a deep learning algorithm performs as well as an abdominal radiologist in detecting clinically significant prostate cancer on MRI.
Exploring robotic surgery in pediatric general surgery, the review highlights benefits such as improved precision and reduced recovery times, despite challenges like instrument size and high costs. Future advancements aim to address these issues, offering enhanced outcomes and accessibility for pediatric patients.
A team of researchers has developed an AI-powered application that analyzes surgical technique videos and provides feedback, enhancing the training process for surgeons.
In a study published in Scientific Reports, a team led by Associate Professor Hideyuki Kobayashi of the Department of Urology, Toho University School of Medicine, Tokyo, Japan, created an AI model that can predict the risk of male infertility with no need for semen analysis by measuring hormone levels in a blood test.
Researchers found that using autonomous AI for diabetic eye disease (DED) testing in primary care settings significantly improved testing adherence and health equity. At AI-implemented sites, adherence to annual eye exams increased, particularly for disadvantaged groups, highlighting AI's potential to enhance healthcare access and prevent vision loss from diabetes.
Terms
While we only use edited and approved content for Azthena
answers, it may on occasions provide incorrect responses.
Please confirm any data provided with the related suppliers or
authors. We do not provide medical advice, if you search for
medical information you must always consult a medical
professional before acting on any information provided.
Your questions, but not your email details will be shared with
OpenAI and retained for 30 days in accordance with their
privacy principles.
Please do not ask questions that use sensitive or confidential
information.
Read the full Terms & Conditions.