A5041175834- Biomedical Text Mining and Ontologies
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare and Education
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Electronic Health Records Systems
- Health Systems, Economic Evaluations, Quality of Life
- Pharmacovigilance and Adverse Drug Reactions
- Advanced Causal Inference Techniques
- Artificial Intelligence in Healthcare
- COVID-19 Clinical Research Studies
- Topic Modeling
- Computational Drug Discovery Methods
- Statistical Methods in Clinical Trials
- Healthcare cost, quality, practices
- Gene expression and cancer classification
- Natural Language Processing Techniques
- Ethics in Clinical Research
- Medical Coding and Health Information
- Long-Term Effects of COVID-19
- Chronic Disease Management Strategies
- SARS-CoV-2 and COVID-19 Research
- Radiomics and Machine Learning in Medical Imaging
- Genetics, Bioinformatics, and Biomedical Research
- Healthcare Policy and Management
Stanford University
2016-2025
Stanford Medicine
2015-2025
Stanford Health Care
2015-2025
Digital Science (United States)
2024
Cardiovascular Institute of the South
2024
Palo Alto University
2019-2024
Kantipur Engineering College
2024
Artificial Intelligence in Medicine (Canada)
2024
Mayo Clinic in Arizona
2023
Clinical Practice Research Datalink
2023
Abstract Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variables from normalized EHR data, a labor-intensive process that discards the vast majority information in each patient’s record. We propose representation patients’ entire raw records based on Fast Healthcare Interoperability Resources (FHIR) format....
We need to consider the ethical challenges inherent in implementing machine learning health care if its benefits are be realized. Some of these straightforward, whereas others have less obvious risks but raise broader concerns.
The vision of creating accessible, reliable clinical evidence by accessing the clincial experience hundreds millions patients across globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from Medical Outcomes Partnership to turn methods research insights into suite applications exploration tools that move field closer ultimate goal generating about all aspects healthcare serve needs patients, clinicians other decision-makers around world.
Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, annotation, natural-language processing and decision support. BioPortal (http://bioportal.bioontology.org) is an open repository of biomedical that provides access via Web services browsers developed in OWL, RDF, OBO format Protégé frames. functionality includes the ability browse, search visualize ontologies. The interface also facilitates community-based participation evaluation...
As of April 3, 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had caused 972 303 cases disease 2019 (COVID-19) and 50 322 deaths worldwide. 1Early reports from China suggested that coinfection with other pathogens was rare. If this were the case, patients positive for might be assumed unlikely to have SARS-CoV-2.The Centers Disease Control Prevention endorsed testing pathogens, suggesting evidence another infection could aid evaluation potential COVID-19 in absence widely...
The National Center for Biomedical Ontology (NCBO) is one of the Centers Computing funded under NIH Roadmap Initiative. Contributing to national computing infrastructure, NCBO has developed BioPortal, a web portal that provides access library biomedical ontologies and terminologies ( http://bioportal.bioontology.org ) via Web services. BioPortal enables community participation in evaluation evolution ontology content by providing features add mappings between terms, comments linked specific...
SARS-CoV-2-specific antibodies, particularly those preventing viral spike receptor binding domain (RBD) interaction with host angiotensin-converting enzyme 2 (ACE2) receptor, can neutralize the virus. It is, however, unknown which features of serological response may affect clinical outcomes COVID-19 patients. We analyzed 983 longitudinal plasma samples from 79 hospitalized patients and 175 SARS-CoV-2-infected outpatients asymptomatic individuals. Within this cohort, 25 died their illness....
In this Viewpoint, Verghese and colleagues discuss the promise challenges of integrating artificial intelligence (AI) into clinical care argue that AI will always need guidance by physicians if it is to improve patients.
Background and Aims Proton pump inhibitors (PPIs) have been associated with adverse clinical outcomes amongst clopidogrel users after an acute coronary syndrome. Recent pre-clinical results suggest that this risk might extend to subjects without any prior history of cardiovascular disease. We explore potential in the general population via data-mining approaches. Methods Using a novel approach for mining data pharmacovigilance, we queried over 16 million documents on 2.9 individuals examine...
Access to palliative care is a key quality metric which most healthcare organizations strive improve. The primary challenges increasing access are combination of physicians over-estimating patient prognoses, and shortage staff in general. This, with treatment inertia can result mismatch between wishes, their actual towards the end life. In this work, we address problem, Institutional Review Board approval, using machine learning Electronic Health Record (EHR) data patients. We train Deep...
Signal-detection algorithms (SDAs) are recognized as vital tools in pharmacovigilance. However, their performance characteristics generally unknown. By leveraging a unique gold standard recently made public by the Observational Medical Outcomes Partnership (OMOP) and conducting systematic evaluation, we provide new insights into diagnostic potential of SDAs that routinely applied to US Food Drug Administration (FDA) Adverse Event Reporting System (AERS). We find can attain reasonable...
The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading the use classification prediction models health care enhance clinical decision-making for diagnosis, treatment prognosis. However, such advances are limited by lack reporting standards used develop those models, model architecture, evaluation validation processes. Here, we present MINIMAR (MINimum Information Medical AI Reporting), a proposal describing minimum...
The National Center for Biomedical Ontology is now in its seventh year. goals of this Computing are to: create and maintain a repository biomedical ontologies terminologies; build tools web services to enable the use terminologies clinical translational research; educate their trainees scientific community broadly about ontology ontology-based technology best practices; collaborate with variety groups who develop biomedicine. centerpiece web-based resource known as BioPortal. BioPortal makes...
Background— Proton pump inhibitors (PPIs) are gastric acid–suppressing agents widely prescribed for the treatment of gastroesophageal reflux disease. Recently, several studies in patients with acute coronary syndrome have raised concern that use PPIs these may increase their risk major adverse cardiovascular events. The mechanism this possible effect is not known. Whether general population might also be at has been addressed. Methods and Results— Plasma asymmetrical dimethylarginine (ADMA)...
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Adverse drug events cause substantial morbidity and mortality are often discovered after a comes to market. We hypothesized that Internet users may provide early clues about adverse via their online information-seeking. conducted large-scale study of Web search log data gathered during 2010. pay particular attention the specific pairing paroxetine pravastatin, whose interaction was reported hyperglycemia time period logs used in analysis. also examine sets pairs known be associated with...
There is an urgent need for biomarkers to better stratify patients with idiopathic pulmonary fibrosis by risk lung transplantation allocation who have the same clinical presentation. We aimed investigate whether a specific immune cell type from could identify those at higher of poor outcomes. then sought validate our findings using cytometry and electronic health records.
Abstract Identification of adverse drug reactions (ADRs) during the post-marketing phase is one most important goals safety surveillance. Spontaneous reporting systems (SRS) data, which are mainstay traditional surveillance, used for hypothesis generation and to validate newer approaches. The publicly available US Food Drug Administration (FDA) Adverse Event Reporting System (FAERS) data requires substantial curation before they can be appropriately, applying different strategies cleaning...
There is increased interest in and potential benefits from using large language models (LLMs) medicine. However, by simply wondering how the LLMs applications powered them will reshape medicine instead of getting actively involved, agency shaping these tools can be used lost.Applications are increasingly to perform medical tasks without underlying model being trained on records verifying their purported benefit performing those tasks.The creation use need shaped provisioning relevant...