Publications by authors named "A W Saenz"

Silicosis, a fibrotic lung disease caused by crystalline silica inhalation, presents unique challenges in lung transplantation. This case reports an unprecedented complication in a lung transplant recipient with chronic silicosis. A man in his 60 s, post left single-lung transplantation for silica-induced pneumoconiosis, developed acute respiratory deterioration following routine bronchoscopy.

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Given the rapidly expanding capabilities of generative AI models for radiology, there is a need for robust metrics that can accurately measure the quality of AI-generated radiology reports across diverse hospitals. We develop ReXamine-Global, a LLM-powered, multi-site framework that tests metrics across different writing styles and patient populations, exposing gaps in their generalization. First, our method tests whether a metric is undesirably sensitive to reporting style, providing different scores depending on whether AI-generated reports are stylistically similar to ground-truth reports or not.

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Autoimmune encephalitis is a disorder characterized by an autoantibody-mediated process that leads to brain inflammation. It is associated with neurological symptoms including cognitive issues, psychiatric problems, seizures, and autonomic dysfunctions. Anti-leucine-rich glioma-inactivated 1 limbic encephalitis (anti-LGI1 LE) is a rare type of autoimmune LE with a unique presentation, comprising neuropsychiatric disturbances, sleep disorders, and faciobrachial dystonic seizures (FBDS).

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Many integrable stochastic particle systems in one space dimension (such as TASEP-Totally Asymmetric Simple Exclusion Process-and its -deformation, the -TASEP) remain integrable if we equip each particle with its own speed parameter. In this work, we present intertwining relations between Markov transition operators of particle systems which differ by a permutation of the speed parameters. These relations generalize our previous works (Petrov and Saenz in Probab Theory Relat Fields 182:481-530, 2022), (Petrov in SIGMA 17(021):34, 2021), but here we employ a novel approach based on the Yang-Baxter equation for the higher spin stochastic six vertex model.

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This report presents a comprehensive case study for the responsible integration of artificial intelligence (AI) into healthcare settings. Recognizing the rapid advancement of AI technologies and their potential to transform healthcare delivery, we propose a set of guidelines emphasizing fairness, robustness, privacy, safety, transparency, explainability, accountability, and benefit. Through a multidisciplinary collaboration, we developed and operationalized these guidelines within a healthcare system, highlighting a case study on ambient documentation to demonstrate the practical application and challenges of implementing generative AI in clinical environments.

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