Promoting breast health awareness: Can a sensor-enabled training system for patient education help?

Introduction: According to a 2009 study published in the Journal of Clinical Oncology, 79% of women (N = 222) diagnosed with breast cancer reported that they identified their cancers through breast self-exam (BSE). However, the U.S.

Generating Rare Surgical Events Using CycleGAN: Addressing Lack of Data for Artificial Intelligence Event Recognition.

Introduction: Artificial Intelligence (AI) has shown promise in facilitating surgical video review through automatic recognition of surgical activities/events. There are few public video data sources that demonstrate critical yet rare events which are insufficient to train AI for reliable video event recognition. We suggest that a generative AI algorithm can create artificial massive bleeding images for minimally invasive lobectomy that can be used to augment the current lack of data in this field.

AI-Based Video Segmentation: Procedural Steps or Basic Maneuvers?

Introduction: Video-based review of surgical procedures has proven to be useful in training by enabling efficiency in the qualitative assessment of surgical skill and intraoperative decision-making. Current video segmentation protocols focus largely on procedural steps. Although some operations are more complex than others, many of the steps in any given procedure involve an intricate choreography of basic maneuvers such as suturing, knot tying, and cutting.

Do Individual Surgeon Preferences Affect Procedural Outcomes?

Objectives: Surgeon preferences such as instrument and suture selection and idiosyncratic approaches to individual procedure steps have been largely viewed as minor differences in the surgical workflow. We hypothesized that idiosyncratic approaches could be quantified and shown to have measurable effects on procedural outcomes.

Methods: At the American College of Surgeons (ACS) Clinical Congress, experienced surgeons volunteered to wear motion tracking sensors and be videotaped while evaluating a loop of porcine intestines to identify and repair 2 preconfigured, standardized enterotomies.

Diversity, equity, and inclusion in presidential leadership of academic medical and surgical societies.

Background: Our aim was to identify gender and racial disparities in presidential leadership for national medical and surgical organizations.

Methods: We located publicly sourced information on national medical organizations. Years between or since the first diverse presidents were analyzed using descriptive statistics and Mann Whitney U tests.

Developing a longitudinal database of surgical skills performance for practicing surgeons: A formal feasibility and acceptance inquiry.

Background: We explored the feasibility and surgeons' perceptions of the utility of a longitudinal skills performance database.

Methods: A 10-station surgical skills assessment center was established at a national scientific meeting. Skills assessment volunteers (n = 189) completed a survey including opinions on practicing surgeons' skills evaluation, ethics, and interest in a longitudinal database.

Can Deep Learning Algorithms Help Identify Surgical Workflow and Techniques?

Background: Surgical videos are now being used for performance review and educational purposes; however, broad use is still limited due to time constraints. To make video review more efficient, we implemented Artificial Intelligence (AI) algorithms to detect surgical workflow and technical approaches.

Methods: Participants (N = 200) performed a simulated open bowel repair.

Performance assessment using sensor technology.

Over the past 30 years, there have been numerous, noteworthy successes in the development, validation, and implementation of clinical skills assessments. Despite this progress, the medical profession has barely scratched the surface towards developing assessments that capture the true complexity of hands-on skills in procedural medicine. This paper highlights the development implementation and new discoveries in performance metrics when using sensor technology to assess cognitive and technical aspects of hands-on skills.

Multimodal Cardiopulmonary Bypass Skills Assessment Within a High-Fidelity Simulation Environment.

Background: A high-fidelity simulator that uses a perfused porcine heart, cannulae, and tubing has been demonstrated to be a useful training adjunct. We hypothesized that multimodal assessment of cardiopulmonary bypass (CPB) skills within this high-fidelity simulated environment could discern expert from trainee performance.

Methods: Three traditional fellows (postgraduate year 6-8) and 3 attending surgeons each performed 3 aortic cannulations.

Translating motion tracking data into resident feedback: An opportunity for streamlined video coaching.

Background: We hypothesized that differences in motion data during a simulated laparoscopic ventral hernia repair (LVH) can be used to stratify top and lower tier performers and streamline video review.

Materials And Methods: Surgical residents (N = 94) performed a simulated partial LVH repair while wearing motion tracking sensors. We identified the top ten and lower ten performers based on a final product quality score (FPQS) of the repair.

Use of sensors to quantify procedural idle time: Validity evidence for a new mastery metric.

Background: Quantification of mastery is the first step in using objective metrics for teaching. We hypothesized that during orotracheal intubation, top tier performers have less idle time compared to lower tier performers.

Methods: At the Anesthesiology 2018 Annual Meeting, 82 participants intubated a normal airway simulator and a burnt airway simulator.

Screening surgical residents' laparoscopic skills using virtual reality tasks: Who needs more time in the sim lab?

Background: This study investigated the possibility of using virtual reality perceptual-motor tasks as a screening tool for laparoscopic ability. We hypothesized that perceptual-motor skills assessed using virtual reality will correlate with the quality of simulated laparoscopic ventral hernia repair.

Materials And Methods: Surgical residents (N = 37), performed 2 virtual reality perceptual-motor tasks: (1) force matching and (2) target tracking.

Residents' surgical performance during the laboratory years: an analysis of rule-based errors.

Background: Nearly one-third of surgical residents will enter into academic development during their surgical residency by dedicating time to a research fellowship for 1-3 y. Major interest lies in understanding how laboratory residents' surgical skills are affected by minimal clinical exposure during academic development. A widely held concern is that the time away from clinical exposure results in surgical skills decay.