Biography and Research Information
OverviewAI-generated summary
Shih's research interests encompass the intersection of health literacy and patient outcomes, as well as the application of advanced machine learning techniques for personalized recommendations. Their work in health literacy focuses on understanding how accessible health information can "level the playing field" for dermatology patients, aiming to improve health equity. In parallel, Shih investigates the efficacy of deep learning models, specifically "Deep vs. Wide & Deep Learners," when applied as contextual bandits for optimizing personalized email promotional strategies. This dual focus highlights an interest in both improving patient understanding and leveraging data science for targeted engagement. Shih has a scholarly profile with an h-index of 4, reflecting 28 total publications and 218 citations.
Metrics
- h-index: 4
- Publications: 28
- Citations: 218
Selected Publications
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Health Literacy in Dermatology Patients: How to Level the Playing Field (2022)
Collaboration Network
Top Collaborators
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
- Evaluating Deep Vs. Wide & Deep Learners As Contextual Bandits For Personalized Email Promo Recommendations
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