Big Tech bets on AI narratives to stave off US break-ups begin paying dividend | MLex | Specialist news and analysis on legal risk and regulation

Google recently dodged corporate dismemberment in US federal court, in part, thanks to one District of Columbia federal judge’s “hope” that AI industry innovation will prevent the need for what he described as “an incredibly messy and highly risky break-up” that the US Department of Justice proposed as a solution to the tech giant’s monopolistic conduct in Internet search and search advertising markets. The decision is likely welcome news for Meta Platforms, which is banking on arguments about AI innovation in its fight against a break-up bid from US Federal Trade Commission antitrust litigation targeting Facebook’s acquisitions of WhatsApp and Instagram.

Assessment of artificial intelligence-aided X-ray in diagnosis of bone fractures in emergency setting – Egyptian Journal of Radiology and Nuclear Medicine

Introduction Fractures pose a critical challenge in emergency settings, necessitating rapid and accurate diagnosis to prevent complications. Recent advances in artificial intelligence (AI) have opened new possibilities for fracture detection using X-ray imaging. This study aimed to evaluate the performance of SmartUrgence® by Milvue, an AI tool designed to identify fractures in emergency cases, comparing its results to computed tomography (CT) scans, the gold standard in fracture diagnosis. Methods Patients referred from the Orthopedic Department after clinical suspicion of fractures underwent both AI-assisted X-ray imaging and CT scans. The study compared AI-generated X-ray assessments with CT scan findings to measure the AI tool’s accuracy, sensitivity, and specificity. Results SmartUrgence® demonstrated strong diagnostic metrics: specificity of 95.45%, sensitivity of 91.13%, positive predictive value (PPV) of 93.39%, and negative predictive value (NPV) of 93.85%. Overall accuracy reached 93.67%, with a balanced accuracy of 93.25%. Precision (0.934) and recall (0.911) were also high, reflecting the AI’s ability to minimize false positives and negatives. However, the AI tool’s performance remained significantly different from that of CT scans (P