The most effective way to harness the power of artificial intelligence (AI) when screening for breast cancer may be through collaboration with human radiologists - not by wholesale replacing them, says new research co-written by a University of Illinois Urbana-Champaign expert in the intersection of health care and technology.
A team of researchers from the Department of Diagnostic and Therapeutic Ultrasonography at the Tianjin Medical University Cancer Institute & Hospital, have published a review in Cancer Biology & Medicine. The paper underscores the potential of AI to decode complex biological data with unprecedented speed and accuracy.
JMIR Biomedical Engineering is inviting submissions for a new section titled "AI Applications in Biomedical Engineering." This themed section explores the integration of biomedical engineering and artificial intelligence (AI), focusing on how AI's capabilities are changing health care.
Investigators of the Vall d'Hebron Institute of Oncology's (VHIO) Radiomics Group, led by Raquel Perez-Lopez, have developed SALSA (System for Automatic Liver tumor Segmentation And detection), a fully automated deep learning-driven tool for the precise and completely automated detection and monitoring of liver tumors (hepatocellular carcinoma).
Klinikum Region Hannover (KRH) has commissioned Siemens Healthineers to install infection control system (ICS) at the Klinikum Siloah hospital. The ICS aims to effectively tackle nosocomial infections and increase patient and employee safety. The systems detect and record potential pathogen sources and trigger automated processes to take the right measures at the right time.
A new study led by investigators at the UCLA Health Jonsson Comprehensive Cancer Center suggests that artificial intelligence (AI) could help detect interval breast cancers - those that develop between routine screenings - before they become more advanced and harder to treat.
A new review, published in the peer-reviewed journal AI in Precision Oncology, explores the multifaceted reasons behind the skepticism surrounding artificial intelligence (AI) technologies in healthcare and advocates for approaches to build confidence in AI applications.
Artificial intelligence (AI) shows tremendous promise for analyzing vast medical imaging datasets and identifying patterns that may be missed by human observers. AI-assisted interpretation of brain scans may help improve care for children with brain tumors called gliomas, which are typically treatable but vary in risk of recurrence.
A new technology partnership formally announced, could help NHS, local government, and housing organisations collaborate to create an unprecedented understanding of the risks and needs of people in their care. Resulting intelligence could enable co-ordinated decisions that help to ease demand on recovering NHS services, prevent avoidable harm and A&E visits, and target community interventions where they can make the biggest impact for individuals.
Each year, more than three million people worldwide are treated with stents to open blocked blood vessels caused by heart disease. However, monitoring the healing process after implantation remains a challenge. If the tissue growing over the stent develops irregularly - either becoming too thick or forming deposits - it can lead to complications, such as re-narrowing or occlusion of the blood vessel.