What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Artificial intelligence
- Cancer
His primary scientific interests are in Ontology, Pharmacovigilance, MEDLINE, Data science and Open Biomedical Ontologies.
His work carried out in the field of Ontology brings together such families of science as Controlled vocabulary, Metadata and Data integration.
His Pharmacovigilance study combines topics from a wide range of disciplines, such as The Internet, Data mining, Adverse Event Reporting System and Patient safety.
The study incorporates disciplines such as Health Administration Informatics, IDEF5, Observational Studies as Topic and Health services research in addition to Data science.
His study looks at the intersection of IDEF5 and topics like Ontology for Biomedical Investigations with Bioinformatics.
The concepts of his Open Biomedical Ontologies study are interwoven with issues in Web service and World Wide Web.
His most cited work include:
- The OBO Foundry : coordinated evolution of ontologies to support biomedical data integration (1945 citations)
- Scalable and accurate deep learning with electronic health records (738 citations)
- BioPortal: ontologies and integrated data resources at the click of a mouse (675 citations)
What are the main themes of his work throughout his whole career to date?
Data science, Artificial intelligence, Ontology, Information retrieval and Machine learning are his primary areas of study.
His research in Data science intersects with topics in Event and MEDLINE.
His Ontology study deals with World Wide Web intersecting with Data integration.
His Information retrieval research incorporates themes from Text mining and Set.
His research in Machine learning focuses on subjects like Observational study, which are connected to Cohort, Clinical trial and Cohort study.
His studies deal with areas such as Ontology components, IDEF5 and Semantic Web as well as Open Biomedical Ontologies.
He most often published in these fields:
- Data science (16.67%)
- Artificial intelligence (16.39%)
- Ontology (15.00%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (16.39%)
- Severe acute respiratory syndrome coronavirus 2 (3.06%)
- Emergency medicine (5.83%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Severe acute respiratory syndrome coronavirus 2, Emergency medicine, Cohort study and MEDLINE.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Predictive modelling, Machine learning and Software deployment.
His Cohort study research integrates issues from Kidney disease, Veterans Affairs, Cohort and Pneumonia.
His MEDLINE research is multidisciplinary, relying on both Missing data, Unstructured data and Medical emergency.
His Language model study also includes
- Transfer of learning most often made with reference to Representation,
- Ontology most often made with reference to Key.
His work in Ontology addresses issues such as Health records, which are connected to fields such as Data science.
Between 2019 and 2021, his most popular works were:
- Rates of Co-infection Between SARS-CoV-2 and Other Respiratory Pathogens. (280 citations)
- Defining the features and duration of antibody responses to SARS-CoV-2 infection associated with disease severity and outcome. (76 citations)
- Persistent detection of SARS-CoV-2 RNA in patients and healthcare workers with COVID-19. (31 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Artificial intelligence
- Cancer
His primary areas of investigation include Severe acute respiratory syndrome coronavirus 2, Emergency medicine, Scalability, Young adult and Artificial intelligence.
His Emergency medicine study integrates concerns from other disciplines, such as Viral shedding, Case-control study and Transmission-based precautions.
The concepts of his Scalability study are interwoven with issues in Multimedia, Software portability, Interoperability and Temporality.
He interconnects Logistic regression, Emergency department, Retrospective cohort study, Adult patients and Comorbidity in the investigation of issues within Young adult.
His Artificial intelligence research is multidisciplinary, incorporating elements of Predictive modelling and Target population.
His work carried out in the field of Internal medicine brings together such families of science as Test and Viral infection.
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