Virtual breakout rooms: an effective approach to offer guidance to medical students on residency applications

Implication statement Peer mentorship on residency applications has been difficult due to recent public health measures, prompting a shift from in-person events to virtual platforms. To address gaps in career exploration, we created a virtual, non-recorded space that allowed medical students and residents to discuss the Canadian Resident Matching Service (CaRMS) process meaningfully and transparently. Attendees reported a greater understanding of the match process and reduced anxiety after the event. This model provides a virtual framework that can be adapted for various mentorship opportunities.

Making a match: trends in the application, interview, and ranking process for the neurological surgery residency programs

OBJECTIVE Neurosurgery is a highly competitive residency field with a match rate lower than that of other specialties. The aim of this study was to analyze trends associated with the residency match process from the applicants’ and program directors’ perspectives. METHODS Between 2010 and 2020, the National Residency Matching Program (NRMP) Applicant and Program Director Surveys, the NRMP Charting Outcomes reports, and the Accreditation Council for Graduate Medical Education (ACGME) Data Resource Books were analyzed to identify the number of applicants interviewed and ranked in US programs, the applicants’ ranking preferences, the program directors’ preferential factors in offering interviews, and rank list order. Applicants were divided between US senior medical students and independent applicants. Each cohort was dichotomized for matched and unmatched applicants. RESULTS Over the study period, 2935 applicants applied to neurosurgery residency, including 2135 US senior medical students and 800 independent applicants, with an overall match rate of 65%. Overall, matched applicants had a significantly higher number of publications (p < 0.05). Among US senior medical student applicants, the application-to-interview ratio more than doubled over the study period, yet the number of interview invitations received, interviews accepted, and programs ranked remained unchanged. In the US senior medical student cohort, the number of submitted applications, interview invitations, accepted interviews, and programs ranked did not significantly differ between matched and unmatched applicants. In both cohorts, applicants shifted ranking factors from a more academic focus in early years to more well-being in later years. Letters of recommendation and board scores were key factors for program directors while screening applicants for interviews and ranking. CONCLUSIONS Neurosurgery residency continues to be a highly competitive field in medicine, with match rates of 65%. Recently, applicants have placed greater importance on ranking programs that value residents’ well-being, as opposed to strictly academic factors. A data-driven understanding of factors important to applicants and program directors during the match process has the potential to improve resident candidate recruitment and overall resident-program fit, thereby improving well-being during residency, reducing the attrition rate, and overall enhancing the diversity of the neurosurgery resident workforce.

Star Identification Based on Multilayer Voting Algorithm for Star Sensors

This paper describes the multilayer voting algorithm, a novel autonomous star identification method for spacecraft attitude determination. The proposed algorithm includes two processes: an initial match process and a verification process. In the initial match process, a triangle voting scheme is used to acquire candidates of the detected stars, in which the triangle unit is adopted as the basic voting unit. During the identification process, feature extraction is implemented, and each triangle unit is described by its singular values. Then the singular values are used to search for candidates of the imaged triangle units, which further improve the efficiency and robustness of the algorithm. After the initial match step, a verification method is applied to eliminate incorrect candidates from the initial results and then outputting the final match results of the imaged stars. Experiments show that our algorithm has more robustness to position noise, magnitude noise, and false stars than the other three algorithms, the identification speed of our algorithm is largely faster than the geometric voting algorithm and optimized grid algorithm. However, it takes more memory, and SVD also seems faster.