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While large language models (LLMs) have been widely used to assist clinicians and support patients, no existing work has explored dialogue systems for standard diagnostic interviews and assessments. This study aims to bridge the gap in mental healthcare accessibility by developing an LLM-powered dialogue system that replicates clinician behavior.

Prior studies often examine single telehealth encounter types or aggregate all digital care, overlooking how patients combine multiple digital and in-person modalities in hybrid care. To address this gap, we derived hybrid care engagement phenotypes and assessed sociodemographic differences and associations with glycemic control among adults with type 2 diabetes (T2DM).

We evaluated bidirectional long short-term memory models for predicting inpatient mortality using different approaches to processing vital signs data collected during the initial 24 h of intensive care unit (ICU) admissions.

To optimise the identification of patients presenting with pain in emergency department (ED) settings with limited resources using multiple transfer learning techniques.

The use of ambient AI documentation tools is rapidly growing in US hospitals and clinics. Such tools generate the first draft of clinical notes from scribed patient-provider conversations, which clinicians can then review and edit before signing into electronic health records (EHR). Understanding how and why clinicians make modifications to AI-generated drafts is critical to improving AI design and clinical efficiency, yet it has been under-studied. This study aims to [...]

Biobanks are essential for intelligent medicine but face fragmentation and heterogeneity. No standardized framework exists for assessing biobank data value using public information; this study addresses this gap.

Using 15 years of hospital survey data (2008-2023), we examined rural-urban trends in electronic health records (EHR) adoption and advanced capabilities for data sharing, public health reporting, and care improvements.

This review aims to identify the contribution of user experience features and underlying technical features to sustained engagement in unguided chatbots for improving health-related behaviors.

Charles Friedman's Fundamental Theorem of Biomedical Informatics holds that a person working in partnership with an information resource outperforms that same person unassisted. Since its publication, advances in artificial intelligence (AI), adaptive learning systems, and large-scale data infrastructures have transformed the biomedical ecosystem, extending informatics beyond clinical care into domains such as public health, consumer health, translational science, and the broader life sciences. Such expansion has further underscored the importance [...]

This study examined whether attendance at online digital health research appointments in the American Women Assessing Risk Epidemiologically (AWARE) study was associated with (1) participant age, (2) scheduling factors (time of day, day of week, month), (3) appointment confirmation, and (4) HIV behavioral risk factors.