Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.

Purpose: Automated machine learning (AutoML) has emerged as a novel tool for medical professionals lacking coding experience, enabling them to develop predictive models for treatment outcomes. This study evaluated the performance of AutoML tools in developing models predicting the success of pneumatic retinopexy (PR) in treatment of rhegmatogenous retinal detachment (RRD). These models were then compared with custom models created by machine learning (ML) experts. Design: Retrospective multicenter study. Participants: Five hundred and thirty nine consecutive patients with primary RRD that underwent PR by a vitreoretinal fellow at 6 training hospitals between 2002 and 2022. Methods: We used 2 AutoML platforms: MATLAB Classification Learner and Google Cloud AutoML. Additional models were developed by computer scientists. We included patient demographics and baseline characteristics, including lens and macula status, RRD size, number and location of breaks, presence of vitreous hemorrhage and lattice degeneration, and physicians' experience. The dataset was split into a training (n = 483) and test set (n = 56). The training set, with a 2:1 success-to-failure ratio, was used to train the MATLAB models. Because Google Cloud AutoML requires a minimum of 1000 samples, the training set was tripled to create a new set with 1449 datapoints. Additionally, balanced datasets with a 1:1 success-to-failure ratio were created using Python. Main Outcome Measures: Single-procedure anatomic success rate, as predicted by the ML models. F2 scores and area under the receiver operating curve (AUROC) were used as primary metrics to compare models. Results: The best performing AutoML model (F2 score: 0.85; AUROC: 0.90; MATLAB), showed comparable performance to the custom model (0.92, 0.86) when trained on the balanced datasets. However, training the AutoML model with imbalanced data yielded misleadingly high AUROC (0.81) despite low F2-score (0.2) and sensitivity (0.17). Conclusions: We demonstrated the feasibility of using AutoML as an accessible tool for medical professionals to develop models from clinical data. Such models can ultimately aid in the clinical decision-making, contributing to better patient outcomes. However, outcomes can be misleading or unreliable if used naively. Limitations exist, particularly if datasets contain missing variables or are highly imbalanced. Proper model selection and data preprocessing can improve the reliability of AutoML tools. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Student-run free clinics may enhance medical students' self-confidence in their clinical skills and preparedness for clerkships.

INTRODUCTION: Student-run free clinics (SRFCs) offer medical students a unique opportunity to develop their clinical, diagnostic, and social skills while providing care to medically underserved communities. This study aims to evaluate the value of SRFC involvement on students' self-reported confidence in various clinical domains and satisfaction with their medical education. METHODS: We conducted a single-center retrospective pre-post assessment at an urban academic institution among second- to fourth-year medical students. We administered a 25-item questionnaire capturing the scope of clinic involvement and assessing self-reported confidence in multiple clinical domains following a one-year-long participation in student-run free clinics. RESULTS: Fifty-six students completed the survey. Participation in SRFCs significantly increased self-reported confidence in patient history-taking (p < 0.001), performing oral presentations (p < 0.001) and physical exams (p < 0.001). Students also reported significantly greater confidence in working with translators (p < 0.001) or as part of an interprofessional team (p < 0.001) and understanding the needs of the population served (p < 0.001). Students also found SRCs to significantly improve their confidence in preparedness for clerkships (p < 0.001). SRFC involvement can improve medical students' confidence in their clinical and interpersonal skills and enhance preparedness for clerkships and working with diverse patient groups. CONCLUSION: SRFCs are a useful tool in the medical school curriculum that help bridge the gap between classroom learning and clinic and may encourage practice in medically underserved communities. SRFCs also integrate classroom material and clinical practice, although standardized evaluation metrics need to be developed. SRFCs should be incorporated as a learning experience by medical schools nationwide.

A Feasibility Study on a Portable Vision Device for Patients with Stroke and Brain Tumours.

This prospective, single-centre cohort study aimed to evaluate the impact of a portable vision reading device, OrCam Read, on vision-related quality-of-life and independent functional status in patients with low vision due to stroke or brain tumours. Six patients with poor visual acuity or visual field defects due to a stroke or a brain tumour were enrolled at a U.S. Ophthalmology Department. Participants were trained to use OrCam Read and given a loaner device for the 1 month duration of the study. Various assessments, including daily function tests, the National Eye Institute Visual Function Questionnaire-25, and the 10-item neuro-ophthalmic supplement, were administered at the first and last visits. Patients' experience with the device was evaluated with weekly telephone and end-of-study satisfaction surveys. The main outcome measures were the patient satisfaction with OrCam and the mean assessment scores between enrolment and final visits. The intervention with OrCam significantly improved patients' ability to complete daily tasks and participants reported good satisfaction with the device. The results also show non-significant improvement with distant activities, dependency, and role difficulties. Our findings demonstrate the feasibility of studying vision-related quality-of-life using a portable vision device in this patient population and pave the way for a larger study to validate the results of this study.