Mark Walderhaug
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View article: Using machine learning to improve anaphylaxis case identification in medical claims data
Using machine learning to improve anaphylaxis case identification in medical claims data Open
Objectives Anaphylaxis is a severe life-threatening allergic reaction, and its accurate identification in healthcare databases can harness the potential of “Big Data” for healthcare or public health purposes. Materials and methods This stu…
View article: RETRACTED AND REPLACED: Using machine learning to improve anaphylaxis case identification in medical claims data
RETRACTED AND REPLACED: Using machine learning to improve anaphylaxis case identification in medical claims data Open
Our work suggests machine learning models can perform at similar levels as a previously published expert case-finding algorithm, while also having the potential to improve performance or streamline algorithm construction processes by ident…
View article: Multi-omics investigation on the prognostic and predictive factors in metastatic breast cancer using data from Phase III ribociclib clinical trials: A statistical and machine learning analysis plan
Multi-omics investigation on the prognostic and predictive factors in metastatic breast cancer using data from Phase III ribociclib clinical trials: A statistical and machine learning analysis plan Open
A bstract In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4-year scientific collaboration to find novel radiogenomics-based prognostic and predictive factors for HR+/HER2-metastatic b…
View article: Communicating Regulatory High Throughput Sequencing Data Using BioCompute Objects
Communicating Regulatory High Throughput Sequencing Data Using BioCompute Objects Open
For regulatory submissions of next generation sequencing (NGS) data it is vital for the analysis workflow to be robust, reproducible, and understandable. This project demonstrates that the use of the IEEE 2791-2020 Standard, (BioCompute ob…
View article: Use of a rapid electronic survey methodology to estimate blood donors' potential exposure to emerging infectious diseases: Application of a statistically representative sampling methodology to assess risk in US blood centers
Use of a rapid electronic survey methodology to estimate blood donors' potential exposure to emerging infectious diseases: Application of a statistically representative sampling methodology to assess risk in US blood centers Open
Background Risk assessments of transfusion‐transmitted emerging infectious diseases (EIDs) are complicated by the fact that blood donorsʼ demographics and behaviors can be different from the general population. Therefore, when assessing po…
View article: Enabling precision medicine via standard communication of HTS provenance, analysis, and results
Enabling precision medicine via standard communication of HTS provenance, analysis, and results Open
A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessib…
View article: Enabling Precision Medicine via standard communication of HTS provenance, analysis, and results
Enabling Precision Medicine via standard communication of HTS provenance, analysis, and results Open
A personalized approach based on a patient’s or pathogen’s unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to FAIR guiding princ…
View article: Babesiosis Occurrence among the Elderly in the United States, as Recorded in Large Medicare Databases during 2006–2013
Babesiosis Occurrence among the Elderly in the United States, as Recorded in Large Medicare Databases during 2006–2013 Open
Our study reveals increasing babesiosis occurrence among the U.S. elderly during 2006-2013, with highest rates in the babesiosis-endemic states. The study also shows variation in babesiosis occurrence by age, gender, race, state of residen…