AIMC Topic: Patient Safety
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The need for guardrails with large language models in pharmacovigilance and other medical safety critical settings.
Scientific reports
Jul 31, 2025
Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the issue of "hal...
Minimally invasive surgery: a historical and legal perspective on technological transformation.
Journal of robotic surgery
Jul 21, 2025
Minimally Invasive Surgery (MIS) has experienced a significant evolution over the last 5,000 years, progressing from basic manual methods to sophisticated, robot-assisted approaches. The evolution of minimally invasive surgery (MIS) has been influenc...
Why Clinical Trials Will Fail to Ensure Safe AI.
Journal of medical systems
Jul 17, 2025
Recent reports have raised concerns about emergent behaviors in next-generation artificial intelligence (AI) models. These systems have been documented selectively adapting their behaviors during testing to falsify experimental outcomes and bypass re...
Solicitude toward artificial intelligence among health care providers and its relation to their patient's safety culture in Saudi Arabia.
BMC health services research
Jul 2, 2025
BACKGROUND: The healthcare sector is undergoing a digital transformation, where the integration of Artificial Intelligence (AI) plays a vital role in reshaping healthcare practices. AI technologies promise to improve work procedures, mitigate future ...
Enhanced deep learning framework for real-time instrument detection and tracking in laparoscopic surgery using advanced augmentation and tracking techniques.
Surgical endoscopy
Jun 30, 2025
BACKGROUND: Accurate tracking and enumeration of surgical instruments are critical for patient safety and operational efficiency in laparoscopic procedures. Advanced tracking systems enhance object detection by maintaining instrument identity despite...
SwinCVS: a unified approach to classifying critical view of safety structures in laparoscopic cholecystectomy.
International journal of computer assisted radiology and surgery
Apr 11, 2025
PURPOSE: Laparoscopic cholecystectomy is one of the most commonly performed surgeries in the UK. Despite its safety, the volume of operations leads to a notable number of complications, with surgical errors often mitigated by the critical view of saf...
Safety and Precision AI for a Modern Digital Health System.
Yearbook of medical informatics
Apr 8, 2025
Artificial intelligence (AI) promises to revolutionize healthcare. Currently there is a proliferation of new AI applications that are being developed and beginning to be deployed across many areas in healthcare to streamline and make healthcare proce...
Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy.
International journal of computer assisted radiology and surgery
Apr 3, 2025
PURPOSE: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, ...
Developing a deep learning model for the automated monitoring of acupuncture needle insertion: enhancing safety in traditional acupuncture practices.
BMC complementary medicine and therapies
Mar 18, 2025
BACKGROUND: Acupuncture is a widely practiced traditional therapy, yet safety concerns, particularly needle breakage and retention, remain critical issues that can lead to complications such as infections, organ injury, or chronic pain. This study ai...
Integration of Virtual Technology and Artificial Intelligence Improves Satisfaction, Patient Safety, and Nursing Workforce Efficiency.
Journal of nursing care quality
Feb 25, 2025
BACKGROUND: Virtual care technology including artificial intelligence (AI) may augment nursing functions creating flexibility in staffing that reduces workforce shortages and enhances patient safety.
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