DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.

Burn wounds are most commonly evaluated through visual inspection to determine surgical candidacy, taking into account burn depth and individualized patient factors. This process, though cost effective, is subjective and varies by provider experience. Deep learning models can assist in burn wound surgical candidacy with predictions based on the wound and patient characteristics.

Artificial Intelligence Applications in Urology: Reporting Standards to Achieve Fluency for Urologists.

The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a narrative review of the literature of artificial intelligence and machine learning in urology and propose a checklist of reporting standards to improve readability and evaluate the current state of the literature.

Road to automating robotic suturing skills assessment: Battling mislabeling of the ground truth.

Objective: To automate surgeon skills evaluation using robotic instrument kinematic data. Additionally, to implement an unsupervised mislabeling detection algorithm to identify potentially mislabeled samples that can be removed to improve model performance.

Methods: Video recordings and instrument kinematic data were derived from suturing exercises completed on the Mimic FlexVR robotic simulator.

Contribution of Toll-Like Receptors and the NLRP3 Inflammasome in Rheumatoid Arthritis Pathophysiology.

Rheumatoid arthritis (RA) is a progressive autoimmune disease that is characterized by inflammation of the synovial joints leading to cartilage and bone damage. The pathogenesis is sustained by the production of pro-inflammatory cytokines including tumor necrosis factor (TNF), interleukin (IL)-1 and IL-6, which can be targeted therapeutically to alleviate disease severity. Several innate immune receptors are suggested to contribute to the chronic inflammation in RA, through the production of pro-inflammatory factors in response to endogenous danger signals.