Novel Machine-Learning Modeling of Facial Trauma Volume With Regional Event and Weather Data.

Objective: Facial trauma volume is difficult to predict accurately. We aim to understand the capacity of climate and regional events to predict daily facial trauma volume. This can provide epidemiologic understanding and subsequently tailor workforce distribution and scheduling.

Correction: Inferring school district learning modalities during the COVID-19 pandemic with a hidden Markov model.

[This corrects the article DOI: 10.1371/journal.pone.

Inferring school district learning modalities during the COVID-19 pandemic with a hidden Markov model.

During the COVID-19 pandemic, many public schools across the United States shifted from fully in-person learning to alternative learning modalities such as hybrid and fully remote learning. In this study, data from 14,688 unique school districts from August 2020 to June 2021 were collected to track changes in the proportion of schools offering fully in-person, hybrid and fully remote learning over time. These data were provided by Burbio, MCH Strategic Data, the American Enterprise Institute's Return to Learn Tracker and individual state dashboards.

Virtual Tumor Boards for Remote Learning in Head and Neck Surgical Oncology.

Importance: In addition to their patient management value, multidisciplinary tumor boards have been recognized as effective learning tools. However, the value of using a virtual tumor board as a learning tool for head and neck surgical oncology fellows has not been studied.

Objective: To describe the structure and content of the American Head and Neck Society (AHNS) Virtual Tumor Board and assess its educational value as perceived by attendees.

Surgical Treatment in Very Advanced (T4b) Adenoid Cystic Carcinoma of the Head and Neck.

Objective: To compare treatment outcomes for T4b head and neck adenoid cystic carcinoma (ACC).

Study Design: Historical cohort study.

Setting: National Cancer Database (NCDB).