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Availability of patient-specific image data, gathered from preoperatively conducted studies, like computed tomography scans and magnetic resonance imaging studies, during a surgical procedure is a key factor for surgical success and patient safety. Several alternative input methods, including recognition of hand gestures, have been proposed for surgeons to interact with medical image viewers during an operation. Previous studies pointed out the need for usability evaluation of these systems.

Despite progress in patient safety, misidentification errors in radiology such as ordering imaging on the wrong anatomic side persist. If undetected, these errors can cause patient harm for multiple reasons, in addition to producing erroneous electronic health records (EHR) data.

This article aims to evaluate adult type 1 diabetes mellitus (T1DM) self-management behaviors (SMBs) related to exercise and alcohol on a survey versus a smartphone app to compare self-reported and self-tracked SMBs, and examine inter- and intrapatient variability.

Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current state of API use for data access and exchange in health care: (1) API use cases and standards; (2) challenges and facilitators for read and write capabilities; and (3) outlook for development of write capabilities.

To design, develop, and evaluate a scalable clinical data normalization pipeline for standardizing unstructured electronic health record (EHR) data leveraging the HL7 Fast Healthcare Interoperability Resources (FHIR) specification.

To implement an open-source tool that performs deterministic privacy-preserving record linkage (RL) in a real-world setting within a large research network.

Electronic health record (EHR) data aggregated from multiple, non-affiliated, sources provide an important resource for biomedical research, including digital phenotyping. Unlike work with EHR data from a single organization, aggregate EHR data introduces a number of analysis challenges.

Precision behavioral medicine techniques integrating wearable ultraviolet radiation (UVR) sensors may help individuals avoid sun exposure that places them at-risk for skin cancer. As a preliminary step in our patient-centered process of developing a just-in-time adaptive intervention, this study evaluated reactions and preferences to UVR sensors among melanoma survivors.

An important component of processing medical texts is the identification of synonymous words or phrases. Synonyms can inform learned representations of patients or improve linking mentioned concepts to medical ontologies. However, medical synonyms can be lexically similar ("dilated RA" and "dilated RV") or dissimilar ("cerebrovascular accident" and "stroke"); contextual information can determine if 2 strings are synonymous. Medical professionals utilize extensive variation of medical terminology, often not evidenced in structured [...]

Most population-based cancer databases lack information on metastatic recurrence. Electronic medical records (EMR) and cancer registries contain complementary information on cancer diagnosis, treatment and outcome, yet are rarely used synergistically. To construct a cohort of metastatic breast cancer (MBC) patients, we applied natural language processing techniques within a semisupervised machine learning framework to linked EMR-California Cancer Registry (CCR) data.