Evolution of artificial intelligence in healthcare: a 30-year bibliometric study.

Introduction: In recent years, the development of artificial intelligence (AI) technologies, including machine learning, deep learning, and large language models, has significantly supported clinical work. Concurrently, the integration of artificial intelligence with the medical field has garnered increasing attention from medical experts. This study undertakes a dynamic and longitudinal bibliometric analysis of AI publications within the healthcare sector over the past three decades to investigate the current status and trends of the fusion between medicine and artificial intelligence.

Molecular mechanism of long chain non coding RNA LINC00511 influencing breast cancer stem cells: Mechanism of VEGFR1 protein.

A comprehensive investigation into the mechanism of VEGFR1 protein in this process was undertaken. Lentivirus-mediated RNA interference was employed to inhibit the expression of LINC00511 in breast cancer cell lines, and changes in breast cancer stem cell markers, including CD44+/CD24-, were monitored using flow cytometry. Additionally, the interaction between VEGFR1 protein and LINC00511 and the activation of its downstream signaling pathway were investigated through co-immunoprecipitation (Co-IP) and Western blot techniques.

Safety-assured high-speed navigation for MAVs.

Micro air vehicles (MAVs) capable of high-speed autonomous navigation in unknown environments have the potential to improve applications like search and rescue and disaster relief, where timely and safe navigation is critical. However, achieving autonomous, safe, and high-speed MAV navigation faces systematic challenges, necessitating reduced vehicle weight and size for high-speed maneuvering, strong sensing capability for detecting obstacles at a distance, and advanced planning and control algorithms maximizing flight speed while ensuring obstacle avoidance. Here, we present the safety-assured high-speed aerial robot (SUPER), a compact MAV with a 280-millimeter wheelbase and a thrust-to-weight ratio greater than 5.

Simultaneous Unbinned Differential Cross-Section Measurement of Twenty-Four Z+jets Kinematic Observables with the ATLAS Detector.

Z boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from standard model predictions. All previous measurements of Z boson production characterize the event properties using a small number of observables and present the results as differential cross sections in predetermined bins.