Emily Leventhal
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View article: Examining State Affective and Cognitive Outcomes Following Brief Mobile Phone-Based Training Sessions to Reduce Anxious Interpretations
Examining State Affective and Cognitive Outcomes Following Brief Mobile Phone-Based Training Sessions to Reduce Anxious Interpretations Open
Background Rates of stress and anxiety are alarmingly high in university communities, but most people do not receive treatment. Mobile health (mHealth) interventions show promise to improve psychological symptoms and increase access to int…
View article: Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study
Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study Open
Background As artificial intelligence and machine learning become increasingly influential in clinical practice, it is critical for future physicians to understand how such novel technologies will impact the delivery of patient care. Objec…
View article: Trajectories of mHealth-Tracked Mental Health and Their Predictors in Female Chronic Pelvic Pain Disorders
Trajectories of mHealth-Tracked Mental Health and Their Predictors in Female Chronic Pelvic Pain Disorders Open
These findings suggest that engaging in MVPA is beneficial to the mental health of females with CPPD. Additionally, this study demonstrates the potential of ambulatory mHealth-based data combined with functional models for delineating inte…
View article: Trajectories of mHealth-tracked mental health symptoms and their predictors in chronic pelvic pain
Trajectories of mHealth-tracked mental health symptoms and their predictors in chronic pelvic pain Open
Background. Female chronic pelvic pain disorders (CPPDs) affect 1 in 7 women worldwide and are characterized by psychosocial comorbidities, including reduced quality of life and 2-10 fold increased risk of depression and anxiety. Despite i…
View article: An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients
An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients Open
Machine learning (ML) has the potential to identify subsets of patients with distinct phenotypes from gene expression data. However, phenotype prediction using ML has often relied on identifying important genes without a systems biology co…
View article: Adapting a mobile anxiety intervention for a university community: Insights from a qualitative analysis
Adapting a mobile anxiety intervention for a university community: Insights from a qualitative analysis Open
Mental health concerns are highly prevalent among university populations, often overwhelming available clinical services. Mobile health (mHealth) interventions can offer low-cost care to large populations without requiring in-person treatm…
View article: Single-cell genomic variation induced by mutational processes in cancer
Single-cell genomic variation induced by mutational processes in cancer Open
How cell-to-cell copy number alterations that underpin genomic instability 1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer 2 , remains understudied. Here, by applying scaled single-cell w…