AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions.
View Article and Find Full Text PDFBackground: Tecovirimat, an antiviral treatment for smallpox, was approved as a treatment for mpox by the European Medicines Agency in January 2022. Approval was granted under "exceptional circumstances" based on effectiveness found in pre-clinical challenge studies in animals and safety studies in humans showing minimal side effects. As clinical efficacy studies are still ongoing, there is currently limited information with regard to the acceptability of tecovirimat to treat mpox.
View Article and Find Full Text PDFHair relaxers are predominantly used by Black women in the United States. It has been recently suggested that exposure to potential endocrine-disrupting compounds from the use of these products may be associated with the development of gynecological and breast cancers and anatomically relevant nonmalignancies. We conducted a systematic literature review using PubMed to identify original studies reporting measures of association between hair relaxer use and relevant adverse outcomes, focusing specifically on Black women in the United States.
View Article and Find Full Text PDFPhase-contrast micro-tomography ([Formula: see text]CT) with synchrotron radiation can aid in the differentiation of subtle density variations in weakly absorbing soft tissue specimens. Modulation-based imaging (MBI) extracts phase information from the distortion of reference patterns, generated by periodic or randomly structured wavefront markers (e.g.
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