What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Statistics
- Surgery
Sebastian Schneeweiss focuses on Internal medicine, Confounding, Propensity score matching, Cohort study and Cohort.
His biological study spans a wide range of topics, including Anesthesia and Surgery.
His Confounding Factors study in the realm of Confounding interacts with subjects such as Causality.
His Propensity score matching research focuses on subjects like Pharmacoepidemiology, which are linked to Alternative medicine.
His studies deal with areas such as Prescription drug, Incidence, Database and Comorbidity as well as Cohort study.
Sebastian Schneeweiss combines subjects such as Intensive care medicine and Hazard ratio with his study of Cohort.
His most cited work include:
- Variable Selection for Propensity Score Models (1253 citations)
- A review of uses of health care utilization databases for epidemiologic research on therapeutics (917 citations)
- Risk of Death in Elderly Users of Conventional vs. Atypical Antipsychotic Medications (770 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Internal medicine, Propensity score matching, Cohort study, Confounding and Cohort.
His research on Internal medicine often connects related topics like Surgery.
The concepts of his Propensity score matching study are interwoven with issues in Matching, Covariate, Database and Observational study.
Cohort study is closely attributed to Comorbidity in his research.
His research investigates the connection between Confounding and topics such as Intensive care medicine that intersect with issues in Randomized controlled trial.
Sebastian Schneeweiss interconnects Odds ratio, Epidemiology and Emergency medicine in the investigation of issues within Confidence interval.
He most often published in these fields:
- Internal medicine (33.81%)
- Propensity score matching (21.53%)
- Cohort study (21.85%)
What were the highlights of his more recent work (between 2018-2021)?
- Internal medicine (33.81%)
- Cohort study (21.85%)
- Propensity score matching (21.53%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Internal medicine, Cohort study, Propensity score matching, Hazard ratio and Type 2 diabetes.
His is doing research in Cohort, Stroke, Heart failure, Disease and Dabigatran, both of which are found in Internal medicine.
In his work, Real world evidence and Intensive care medicine is strongly intertwined with Randomized controlled trial, which is a subfield of Cohort study.
His studies in Propensity score matching integrate themes in fields like Relative risk, Active Comparator, Epidemiology and Confounding.
His Confounding research is multidisciplinary, incorporating elements of Covariate and Pharmacoepidemiology.
His research integrates issues of Canagliflozin and Database in his study of Hazard ratio.
Between 2018 and 2021, his most popular works were:
- Empagliflozin and the Risk of Heart Failure Hospitalization in Routine Clinical Care. (78 citations)
- Risk of serious infections in tocilizumab versus other biologic drugs in patients with rheumatoid arthritis: a multidatabase cohort study (51 citations)
- Fracture Risk After Initiation of Use of Canagliflozin: A Cohort Study (50 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Statistics
- Disease
Sebastian Schneeweiss mostly deals with Internal medicine, Cohort study, Propensity score matching, Randomized controlled trial and Hazard ratio.
His work carried out in the field of Internal medicine brings together such families of science as Multiple comparisons problem and Crossover study.
The study incorporates disciplines such as Tocilizumab, Tofacitinib, Rheumatoid arthritis and Cohort in addition to Cohort study.
The various areas that Sebastian Schneeweiss examines in his Cohort study include Baseline time, Bias reduction, Confounding and Exposure group.
The Propensity score matching study combines topics in areas such as Observational study, Calcium, Database, Covariate and Conditional probability.
His Hazard ratio research is multidisciplinary, incorporating elements of Type 2 diabetes and End stage renal disease, Hemodialysis.
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