Surgical Artificial Intelligence and Innovation Laboratory
News
New Postdoctoral Fellowship Opportunity in Surgical AI at Duke Health System
Join the Surgical Artificial Intelligence and Innovation Laboratory (SAIIL) at Duke Department of Surgery in a groundbreaking project revolutionizing surgery through collaborative AI and surgical video understanding. We seek an enthusiastic postdoctoral candidate with a strong background in machine learning, computer vision, deep learning frameworks, and relevant publications.
This two-year project, with the possibility of extension, offers both computational and clinical aspects, focusing on innovative modeling, ML, and computer vision techniques to transform surgical understanding and assistance. With research and commercialization opportunities, candidates will work with unique datasets, aiming to significantly improve surgical care delivery and quality in various settings.
Surgical Artificial Intelligence and Innovation Laboratory (SAIIL)
The Massachusetts General Hospital Surgical Artificial Intelligence and Innovation Laboratory (SAIIL) is a multidisciplinary group composed of surgeons, engineers, and data scientists who are passionate about redesigning the delivery of surgical care. The team is made up of surgeons in the Massachusetts General Hospital Department of Surgery and scientists from the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (CSAIL). Together, our team has developed tools to help unlock the intraoperative phase of care.
Our primary emphasis is on utilizing computer vision to investigate the intraoperative phase of care through real-time, automated surgical analysis. In other words, we use artificial intelligence (AI) to automatically analyze and interpret videos of operations as they occur. The goal is to teach the AI to understand what is happening in an operation, determine whether the risk for a postoperative complication is high, or even provide surgeons with additional data to improve operating room decisions.
While the field of surgical research has improved its ability to study pre- and postoperative events and risk using claims data and patient registries, the intraoperative phase of care remains difficult to study.
In a review of nationwide data, researchers estimated that major intraoperative adverse events (i.e., accidental damage to bowel or major blood vessels) can occur in 2% of all operations. Approximately 22 million general surgery operations are performed each year in the United States, and 440,000 patients may experience an intraoperative adverse event a year. The cost of hospital admission is 41% higher in these patients, and the consequences of adverse events can impact their quality of life. An expected one-day stay could turn into a month-long hospitalization, additional procedures, prolonged rehabilitation, or a host of other life-altering consequences.
Research Vision and Goals
We will help big data realize personalized medicine for surgical patients. We envision a technology-enabled operating room that pulls data from prior operations for real-time clinical decision-making, much like a GPS for surgeons.
We are building technology as the foundation for a worldwide database of surgical cases. A surgeon learns and improves one operation at a time. An AI system can learn from thousands of cases simultaneously. It allows for collecting, analyzing, and sharing quantitative evidence in real-time across multiple surgeons, a “Collective Surgical Consciousness.”
The goals of our research in surgery are to:
Democratize surgical knowledge
Lower costs
Improve outcomes
Reduce morbidity and mortality
Improve Surgeon’s experience