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Tim Friede (1971-)

Arzt

Name	Tim Friede
Zeit	1971- (Lebensdaten)
Ort	Deutschland
Akademischer Grad bzw. Titel	Dr. sc. hum.
Beruf	Arzt (charakteristischer Beruf) Mathematiker
Variante	T. Friede
Beziehung	Universitätsmedizin Göttingen (Professor für Biostatistik) (2010-)
Weitere Angaben	Methodische Forschungsinteressen liegen in der klinischen Biostatistik mit Schwerpunkt zu Designs für klinische Studien (insbesondere flexible adaptive Designs) und Systematische Reviews, Meta-Analysen
Datensatztyp	Person
GND-Nummer	123130999
Datensatz-ID	123130999
Beteiligt an alle anzeigen Robust confidence intervals for meta-regression with interaction effects Pre-hospital heparin is not associated with infarct vessel patency and mortality in ST-segment elevation myocardial infarction patients with out-of-hospital cardiac arrest Health economic evaluation of blended collaborative care for older multimorbid heart failure patients: study protocol Stakeholders' Perspectives on Current Issues in Data Monitoring Committees Challenges in developing and validating machine learning models for TAVI mortality risk prediction: reply On the role of benchmarking data sets and simulations in method comparison studies Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and assessment of existing guidelines Adherence enhancing interventions for pharmacological and oxygen therapy in patients with COPD: protocol for a systematic review and component network meta-analyses Initial therapeutic anticoagulation with rivaroxaban compared to prophylactic therapy with heparins in moderate to severe COVID-19: results of the COVID-PREVENT randomized controlled trial Blinded sample size recalculation in multiple composite population designs with normal data and baseline adjustments The DZHK research platform: maximisation of scientific value by enabling access to health data and biological samples collected in cardiovascular clinical studies Verknüpfung von randomisierten kontrollierten Studien und Real World Data On the role of benchmarking data sets and simulations in method comparison studies Confidence intervals for discrete data in clinical research by Vivek Pradhan, Ashis K. Gangopadhyay, Sandeep M. Menon, Cynthia Basu, Tathagata Banerjee. Boca Raton, FL: Chapman & Hall/CRC Press. 2022. 240 pages. ISBN: 9781138048980 (hbk). ISBN 9781315169859 (ebk). List price: £99.99 Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores Identification of biomarker-defined populations in precision medicine Regularization approaches in clinical biostatistics: a review of methods and their applications Improving the statistical power of economic experiments using adaptive designs Blinded sample size recalculation in adaptive enrichment designs Implementation, mechanisms of change and contextual factors of a complex intervention to improve interprofessional collaboration and the quality of medical care for nursing home residents: study protocol of the process evaluation of the interprof ACT intervention package Immunotherapy for people with clinically isolated syndrome or relapsing-remitting multiple sclerosis: treatment response by demographic, clinical, and biomarker subgroups (PROMISE)—a systematic review protocol On the role of data, statistics and decisions in a pandemic Improving adaptive seamless designs through Bayesian optimization Authors' response: on the role of data, statistics and decisions in a pandemic Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events Effect of Minocycline on Depressive Symptoms in Patients With Treatment-Resistant Depression : A Randomized Clinical Trial Improving adaptive seamless designs through Bayesian optimization Is there a role for statistics in artificial intelligence? On the role of data, statistics and decisions in a pandemic Classification of Companion Diagnostics: A New Framework for Biomarker-Driven Patient Selection Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning Is there a role for statistics in artificial intelligence? Phase I dose-escalation oncology trials with sequential multiple schedules Correction to: Development and evaluation of an interactive web-based decision-making programme on relapse management for people with multiple sclerosis (POWERMS2)—study protocol for a randomised controlled trial Identification of subgroup effect with an individual participant data meta-analysis of randomised controlled trials of three different types of therapist-delivered care in low back pain Development and evaluation of an interactive web-based decision-making programme on relapse management for people with multiple sclerosis (POWERMS2)—study protocol for a randomised controlled trial Bounds for the weight of external data in shrinkage estimation Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations Classification of Companion Diagnostics : A New Framework for Biomarker-Driven Patient Selection Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events Is there a role for statistics in artificial intelligence? Precise variant interpretation, phenotype ascertainment, and genotype-phenotype correlation of children in the EARLY PRO‐TECT Alport trial Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) - estimation of adverse event risks Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): rationale and statistical concept of a meta‐analytic study Effects of strategies to improve general practitioner-nurse collaboration and communication in regard to hospital admissions of nursing home residents (interprof ACT): study protocol for a cluster randomised controlled trial Impact of COVID-19 outbreak on regional STEMI care in Germany Antibody signatures in patients with histopathologically defined multiple sclerosis patterns Multiple Sklerose in Deutschland: aktualisierte Auswertungen des MS-Registers der DMSG 2014–2018 Multiple Sklerose in Deutschland: aktualisierte Auswertungen des MS-Registers der DMSG 2014–2018 Exact change point detection with improved power in small‐sample binomial sequences Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): Rationale and statistical concept of a meta‐analytic study Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data Adaptive seamless clinical trials using early outcomes for treatment or subgroup selection: Methods, simulation model and their implementation in R Impact of COVID-19 outbreak on regional STEMI care in Germany Precise variant interpretation, phenotype ascertainment, and genotype–phenotype correlation of children in the EARLY PRO‐TECT Alport trial Decline of COPD exacerbations in clinical trials over two decades – a systematic review and meta-regression Likelihood-based random-effects meta-analysis with few studies: empirical and simulation studies Quantitative approaches underpinning decision making

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Katalog der Deutschen Nationalbibliothek

Tim Friede (1971-)

Robust confidence intervals for meta-regression with interaction effects

Pre-hospital heparin is not associated with infarct vessel patency and mortality in ST-segment elevation myocardial infarction patients with out-of-hospital cardiac arrest

Health economic evaluation of blended collaborative care for older multimorbid heart failure patients: study protocol

Stakeholders' Perspectives on Current Issues in Data Monitoring Committees

Challenges in developing and validating machine learning models for TAVI mortality risk prediction: reply

On the role of benchmarking data sets and simulations in method comparison studies

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and assessment of existing guidelines

Adherence enhancing interventions for pharmacological and oxygen therapy in patients with COPD: protocol for a systematic review and component network meta-analyses

Initial therapeutic anticoagulation with rivaroxaban compared to prophylactic therapy with heparins in moderate to severe COVID-19: results of the COVID-PREVENT randomized controlled trial

Blinded sample size recalculation in multiple composite population designs with normal data and baseline adjustments

The DZHK research platform: maximisation of scientific value by enabling access to health data and biological samples collected in cardiovascular clinical studies

Verknüpfung von randomisierten kontrollierten Studien und Real World Data

On the role of benchmarking data sets and simulations in method comparison studies

Confidence intervals for discrete data in clinical research by Vivek Pradhan, Ashis K. Gangopadhyay, Sandeep M. Menon, Cynthia Basu, Tathagata Banerjee. Boca Raton, FL: Chapman & Hall/CRC Press. 2022. 240 pages. ISBN: 9781138048980 (hbk). ISBN 9781315169859 (ebk). List price: £99.99

Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores

Identification of biomarker-defined populations in precision medicine

Regularization approaches in clinical biostatistics: a review of methods and their applications

Improving the statistical power of economic experiments using adaptive designs

Blinded sample size recalculation in adaptive enrichment designs

Implementation, mechanisms of change and contextual factors of a complex intervention to improve interprofessional collaboration and the quality of medical care for nursing home residents: study protocol of the process evaluation of the interprof ACT intervention package

Immunotherapy for people with clinically isolated syndrome or relapsing-remitting multiple sclerosis: treatment response by demographic, clinical, and biomarker subgroups (PROMISE)—a systematic review protocol

On the role of data, statistics and decisions in a pandemic

Improving adaptive seamless designs through Bayesian optimization

Authors' response: on the role of data, statistics and decisions in a pandemic

Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events

Effect of Minocycline on Depressive Symptoms in Patients With Treatment-Resistant Depression : A Randomized Clinical Trial

Improving adaptive seamless designs through Bayesian optimization

Is there a role for statistics in artificial intelligence?

On the role of data, statistics and decisions in a pandemic

Classification of Companion Diagnostics: A New Framework for Biomarker-Driven Patient Selection

Design aspects of COVID‐19 treatment trials: Improving probability and time of favorable events

Subgroup identification in individual participant data meta-analysis using model-based recursive partitioning

Is there a role for statistics in artificial intelligence?

Phase I dose-escalation oncology trials with sequential multiple schedules

Correction to: Development and evaluation of an interactive web-based decision-making programme on relapse management for people with multiple sclerosis (POWERMS2)—study protocol for a randomised controlled trial

Identification of subgroup effect with an individual participant data meta-analysis of randomised controlled trials of three different types of therapist-delivered care in low back pain

Development and evaluation of an interactive web-based decision-making programme on relapse management for people with multiple sclerosis (POWERMS2)—study protocol for a randomised controlled trial

Bounds for the weight of external data in shrinkage estimation

Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations

Classification of Companion Diagnostics : A New Framework for Biomarker-Driven Patient Selection

Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events

Estimating and comparing adverse event probabilities in the presence of varying follow‐up times and competing events

Is there a role for statistics in artificial intelligence?

Precise variant interpretation, phenotype ascertainment, and genotype-phenotype correlation of children in the EARLY PRO‐TECT Alport trial

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) - estimation of adverse event risks

Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): rationale and statistical concept of a meta‐analytic study

Effects of strategies to improve general practitioner-nurse collaboration and communication in regard to hospital admissions of nursing home residents (interprof ACT): study protocol for a cluster randomised controlled trial

Impact of COVID-19 outbreak on regional STEMI care in Germany

Antibody signatures in patients with histopathologically defined multiple sclerosis patterns

Multiple Sklerose in Deutschland: aktualisierte Auswertungen des MS-Registers der DMSG 2014–2018

Multiple Sklerose in Deutschland: aktualisierte Auswertungen des MS-Registers der DMSG 2014–2018

Exact change point detection with improved power in small‐sample binomial sequences

Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY): Rationale and statistical concept of a meta‐analytic study

Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data

Adaptive seamless clinical trials using early outcomes for treatment or subgroup selection: Methods, simulation model and their implementation in R

Impact of COVID-19 outbreak on regional STEMI care in Germany

Precise variant interpretation, phenotype ascertainment, and genotype–phenotype correlation of children in the EARLY PRO‐TECT Alport trial

Decline of COPD exacerbations in clinical trials over two decades – a systematic review and meta-regression

Likelihood-based random-effects meta-analysis with few studies: empirical and simulation studies

Quantitative approaches underpinning decision making