Browsing Biomedical and health informatics by Title
Now showing items 72-91 of 100
-
Reconfiguring the Everyday: Understanding, Designing, and Supporting Chronic Illness Management
From taking medications at the right time to emotionally dealing with their symptoms, patients who have a chronic illness must manage many facets of their illness. Today, patients often utilize different types of general-purpose ... -
Reproducibility in human cognitive neuroimaging: a community-driven data sharing framework for provenance information integration and interoperability
Access to primary data and the provenance of derived data are increasingly recognized as an essential aspect of reproducibility in biomedical research. While productive data sharing has become the norm in some biomedical ... -
RNA-seq generates new insights into Leishmania differentiation
Leishmania donovani, an intracellular parasitic trypanosomatid, causes kala-azar, a fatal form of visceral leishmaniasis in humans. Infection occurs through a cycle whereby parasites (promastigote stage) living in the ... -
Secondary Usage of Electronic Health Record Data for Patient-Specific Modeling
Translational research has become an important bridge that moves findings from basic science research to patients' bedside and to the clinical community. Unfortunately, this notion of translational research seems to be ... -
Secondary Use of Electronic Clinical Data: Barriers, Facilitators and a Proposed Solution
(2013-02-25)The increasing adoption of electronic medical records is producing a massive accumulation of routinelly collected electronic clinical data (ECD). This data can be used not only for direct patient care but for secondary ... -
Supporting collaborative clinical trial protocol writing through an annotation design
(2005)Clinical trial protocols are important documents that guide clinical research. Modern protocol development requires collective expertise from a group of Loosely-Coupled protocol writers, who work across distances and time ... -
Supporting collaborative goal-setting for hospitalized adolescent patients
Collaborative goal-setting is an effective way to encourage patient engagement and facilitate patient-provider communication. However, few studies have explored how hospitalized patients understand and use collaborative ... -
Supporting Hospitalized Patients through AI Technologies
Involving hospitalized patients in their care has been shown to be valuable in terms of achieving better health outcomes for them. Therefore, hospitalized patients are encouraged to actively engage in their own care, ... -
The Synthetic Biology Open Language a data exchange standard for biological engineering
(2013-02-25)Synthetic biology is the emerging research and engineering field concerned with the design and construction of new biological functions and systems. Synthetic biologists are engineering organisms to solve outstanding ... -
Temporal Data Mining in Electronic Medical Records from Patients with Acute Coronary Syndrome
(2014-02-24)Every 25 seconds someone in the US has a cardiac event and one person per minute will die from it. ST-elevated myocardial infarction (STEMI), non ST-elevated myocardial infarction and unstable angina are caused by ischemia ... -
Text Mining with Deep Learning for Secondary Use In Radiology
For more than a decade, electronic health records (EHR) have been used extensively in biomedical research. However, structured data, such as diagnoses and procedural codes do not necessarily capture the most precise medical ... -
The Problem of Time: Addressing challenges in spatio-temporal data integration
Across scientific disciplines, an ever-growing proportion of data can be effectively described in spatial terms. As researchers have become comfortable with techniques for dealing with spatial data, the next progression ... -
The Untold Story of Predicting Readmissions for Heart Failure Patients
The availability and accessibility of Electronic Health Record (EHR) data create an opportunity for researchers to revolutionize healthcare. The recognition of the importance of secondary use of EHR data has led to the ... -
The Use of Inter-Clinician Variation in Measuring Healthcare Performance
To monitor and improve healthcare in the US, providers are required to report healthcare measures as part of regulatory and compensatory systems. However, there are growing concerns that the collection and reporting of ... -
The Use of Natural Language Processing and Machine Learning for Early Diagnosis of Lung and Ovarian Cancer
Cancer is a serious diagnosis and diagnostic delay is correlated with reductions in survivalrates following treatment. For many cancers, providers can only rely on symptoms and signs to diagnose patients. These details ... -
U-Net for Cerebral Cortical MR Image Segmentation
Cerebral cortex segmentation from three-dimensional structural Magnetic Resonance (MR) brain images plays an important role in measuring loss of cortical tissues for disorders such as Alzheimer's disease (AD). U-Net, a ... -
Understanding and communicating spatially-oriented ontologies
Ontologies have become increasingly important for both representation of biomedical knowledge and for using that knowledge to facilitate data integration. However, ontologies are generally not presented in ways that are ... -
Understanding Context of Use and Perceptions of Usability of Cosegregation Analysis Tool AnalyzeMyVariant
Calculating the genetic risk for a disease with allelic variants of unknown significance can be a complicated task. AnalyzeMyVariant is a tool designed for genetics experts that uses pedigree data from families with genetic ... -
Understanding Patient and Caregiver Work to Support Health Care System Reliability and Quality
Patients and their families face many challenges navigating and managing their care within hospitals and other healthcare environments. Outside of the stress and anxiety linked to a health crisis, patient and their families ... -
Understanding the differences in cognitively defined subgroups in Alzheimer's disease: A data science approach
My work connects two types of data in Alzheimer’s Disease (AD): structural MRI data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) and cognition data in the form of AD subgroups. The subgroups (AD-Executive, ...