Patients and physicians make essential decisions regarding diagnostic and therapeutic interventions. These actions should be performed or deferred under time constraints and uncertainty regarding patients' diagnoses and predicted response to treatmen...
There is a growing interest in using machine learning algorithms to support surgical care, diagnostics, and public health surveillance in low- and middle-income countries. From our own experience and the literature, we share several lessons for devel...
This review describes the steps and conclusions from the development and validation of an artificial intelligence algorithm (the Hypotension Prediction Index), one of the first machine learning predictive algorithms used in the operating room environ...
In light of recent developments within both health care and robotics, the use of robots within the human body has become attainable. Here we discuss the milestones for the realization of autonomous microrobots in medical applications. The desired tas...
Surgical training has undergone substantial change in the last few decades. As technology and patient complexity continues to increase, demands for novel approaches to ensure competency have arisen. Virtual reality systems augmented with machine lear...
The fields of computer vision (CV) and artificial intelligence (AI) have undergone rapid advancements in the past decade, many of which have been applied to the analysis of intraoperative video. These advances are driven by wide-spread application of...
Automated performance metrics objectively measure surgeon performance during a robot-assisted radical prostatectomy. Machine learning has demonstrated that automated performance metrics, especially during the vesico-urethral anastomosis of the robot-...