Surgical Innovation

Every operation leaves behind a record. Video captures what happened. Vital signs show how the patient responded. Robotic systems record instrument movements. Anesthesia systems capture physiological changes. Yet most of this information remains disconnected once the operation ends. Surgical data science is bringing those signals together. From Surgical Video to Surgical Intelligence AI can now analyze recorded procedures to recognize instruments, anatomical structures, and s

Pancreatic cancer is usually diagnosed too late for curative surgery. More than 85% of patients present with advanced disease, when resection is no longer possible. Researchers at Mayo Clinic have developed an AI model that detects imaging changes months before pancreatic cancer becomes visible on routine CT scans. Looking beyond the tumor The model, called REDMOD, analyzes radiomic features throughout the pancreas instead of searching for a visible mass. In a validation stud

Administrative work remains one of the largest sources of physician workload. Discharge summaries are a prime example, requiring clinicians to accurately document a hospital stay while ensuring continuity of care after discharge. A team at Stanford Medicine evaluated whether an AI assistant could help. AI drafts, physicians approve Researchers developed MedAgentBrief, an AI agent that generated discharge summaries from the electronic health record. During a 10-week pilot in a

Artificial intelligence is becoming part of everyday clinical practice, but evidence on how physicians should use it safely is still catching up. That tension is highlighted in a recent article by The Atlantic, which brings together several new studies on AI-assisted clinical reasoning and the risks of premature adoption. Strong performance does not guarantee safe use In a study published in Science, researchers from Harvard and Stanford found that ChatGPT outperformed hundre

Artificial intelligence is starting to change breast cancer care before treatment even begins. Researchers at UCSF and UC Berkeley used an AI model called Mirai to identify women at high risk immediately after screening mammography and move them into expedited diagnostic evaluation. The workflow reduced diagnostic assessment from weeks to about one hour. Among women diagnosed with breast cancer, the median time to biopsy fell from more than two months to fewer than ten days.

Researchers at the University of Bern have developed an artificial intelligence model that predicts a patient's risk of postoperative infection immediately after surgery, using physiologic data collected during the operation rather than relying only on preoperative risk factors. Why it matters Postoperative infections remain one of the leading causes of surgical complications, contributing to longer hospital stays, higher healthcare costs, and increased mortality. Traditional