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Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

Genet Med

December 2024

Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN. Electronic address:

Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.

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Aim: The purpose of this study is to compare the efficacy of an artificial intelligence (AI)-based care plan learning strategy with standard training techniques in order to determine how it affects nursing students' learning results in newborn resuscitation.

Methods: Seventy third-year nursing students from a state university in Türkiye participated in the study. They were split into two groups: the experimental group, which received care plans based on AI, and the control group, which received traditional instruction.

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Rationale: Chronic pelvic pain syndrome (CPPS) is prevalent and a complex multifactorial condition. The incidence is rising. CPPS patients may benefit from multidisciplinary care in a structured care pathway.

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Voluntary medical male circumcision (VMMC) was identified as an effective strategy in HIV prevention. Although circumcision reduces heterosexual acquisition of HIV by 60%, there is low uptake of VMMC services in Eswatini. This study applies the health belief model (HBM) in understanding perceptions of young men in Eswatini towards VMMC for HIV prevention to upscale its adoption.

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Background: Head and neck cancer (HNC) is amongst the 10 most common cancers worldwide and has a major effect on patients' quality of life. Given the complexity of this unique group of patients, a multidisciplinary team approach is preferable. Amongst the debilitating sequels of HNC and/or its treatment, swallowing, speech and voice impairments are prevalent and require the involvement of speech-language pathologists (SLPs).

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