What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Internal medicine
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Health informatics, Information retrieval and Data science.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Event, Predictive value, Event reporting and Confidence interval.
His Natural language processing research is multidisciplinary, incorporating elements of Event type, Clinical information and Coding.
His Health informatics study combines topics in areas such as Decision support system, Clinical trial, Cohort and Knowledge management.
His Information retrieval research includes themes of Gold standard, Data warehouse, Completeness and MEDLINE.
His studies deal with areas such as Domain, Health Administration Informatics, World Wide Web and Observational Studies as Topic as well as Data science.
His most cited work include:
- Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19. (887 citations)
- Agreement, the F-Measure, and Reliability in Information Retrieval (521 citations)
- Next-generation phenotyping of electronic health records (443 citations)
What are the main themes of his work throughout his whole career to date?
George Hripcsak mainly investigates Artificial intelligence, Observational study, Data science, Natural language processing and MEDLINE.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Vocabulary, Data mining and Process.
George Hripcsak performs integrative Observational study and Informatics research in his work.
His Natural language processing research is multidisciplinary, incorporating perspectives in Terminology and Information retrieval.
He most often published in these fields:
- Artificial intelligence (17.94%)
- Observational study (16.73%)
- Data science (11.49%)
What were the highlights of his more recent work (between 2017-2021)?
- Observational study (16.73%)
- Internal medicine (13.91%)
- Cohort study (9.07%)
In recent papers he was focusing on the following fields of study:
Observational study, Internal medicine, Cohort study, MEDLINE and Cohort are his primary areas of study.
George Hripcsak combines subjects such as Machine learning, Scale, Database and Artificial intelligence with his study of Observational study.
His work deals with themes such as Vocabulary, Set and Natural language processing, which intersect with Artificial intelligence.
His Cohort study study incorporates themes from Kidney disease, Hydroxychloroquine, Adverse effect, Rheumatoid arthritis and Veterans Affairs.
The MEDLINE study combines topics in areas such as Electronic health record, Coronavirus disease 2019, Emergency medicine and Comorbidity.
George Hripcsak has researched Cohort in several fields, including Odds ratio, Breast cancer and Retrospective cohort study.
Between 2017 and 2021, his most popular works were:
- Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19. (887 citations)
- Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series. (255 citations)
- Comprehensive comparative effectiveness and safety of first-line antihypertensive drug classes: a systematic, multinational, large-scale analysis. (79 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Internal medicine
His primary areas of study are Observational study, Internal medicine, Cohort study, MEDLINE and Hazard ratio.
His studies in Observational study integrate themes in fields like Machine learning, Database, Healthcare Cost and Utilization Project, Artificial intelligence and Data quality.
The study incorporates disciplines such as Consistency, Reliability and Process in addition to Artificial intelligence.
His biological study spans a wide range of topics, including Hydroxychloroquine, Adverse effect, Retrospective cohort study, Rheumatoid arthritis and Veterans Affairs.
George Hripcsak has included themes like SNOMED CT, Source data, Natural language processing, Emergency medicine and Coronavirus disease 2019 in his MEDLINE study.
His Data science research integrates issues from Precision medicine, Health informatics and Data sharing.
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