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Jim Parr

Showing results (1-10 of 7) with videos related to

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International Journal for Numerical Methods in Biomedical Engineering|May 11, 2021
A physiologically realistic virtual patient database for the study of arterial haemodynamicsGareth Jones, Jim Parr, Perumal Nithiarasu, et al.
Medical & Biological Engineering & Computing|August 28, 2021
A proof of concept study for machine learning application to stenosis detectionGareth Jones, Jim Parr, Perumal Nithiarasu, et al.
Cureus|May 15, 2025
Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning ModelJim Parr, Van Thai-Paquette, Pearl Paranjape, et al.
Diagnostics (Basel, Switzerland)|February 27, 2026
Machine Learning-Driven Probability Scoring Enhances Diagnostic Certainty and Reduces Costs in Suspected Periprosthetic Joint InfectionJim Parr, Van Thai-Paquette, Amy Worden, et al.
Cureus|December 25, 2023
Achieving High Accuracy in Predicting the Probability of Periprosthetic Joint Infection From Synovial Fluid in Patients Undergoing Hip or Knee Arthroplasty: The Development and Validation of a Multivariable Machine Learning AlgorithmPearl R Paranjape, Van Thai-Paquette, John L Miamidian, et al.
Amyotrophic Lateral Sclerosis & Frontotemporal Degeneration|June 24, 2020
The use of biotelemetry to explore disease progression markers in amyotrophic lateral sclerosisMadeline Kelly, Arseniy Lavrov, Luis Garcia-Gancedo, et al.
JMIR Mhealth and Uhealth|December 21, 2019
Objectively Monitoring Amyotrophic Lateral Sclerosis Patient Symptoms During Clinical Trials With Sensors: Observational StudyLuis Garcia-Gancedo, Madeline L Kelly, Arseniy Lavrov, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
International Journal for Numerical Methods in Biomedical Engineering|May 11, 2021
A physiologically realistic virtual patient database for the study of arterial haemodynamicsGareth Jones, Jim Parr, Perumal Nithiarasu, et al.
Medical & Biological Engineering & Computing|August 28, 2021
A proof of concept study for machine learning application to stenosis detectionGareth Jones, Jim Parr, Perumal Nithiarasu, et al.
Cureus|May 15, 2025
Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning ModelJim Parr, Van Thai-Paquette, Pearl Paranjape, et al.
Diagnostics (Basel, Switzerland)|February 27, 2026
Machine Learning-Driven Probability Scoring Enhances Diagnostic Certainty and Reduces Costs in Suspected Periprosthetic Joint InfectionJim Parr, Van Thai-Paquette, Amy Worden, et al.
Cureus|December 25, 2023
Achieving High Accuracy in Predicting the Probability of Periprosthetic Joint Infection From Synovial Fluid in Patients Undergoing Hip or Knee Arthroplasty: The Development and Validation of a Multivariable Machine Learning AlgorithmPearl R Paranjape, Van Thai-Paquette, John L Miamidian, et al.
Amyotrophic Lateral Sclerosis & Frontotemporal Degeneration|June 24, 2020
The use of biotelemetry to explore disease progression markers in amyotrophic lateral sclerosisMadeline Kelly, Arseniy Lavrov, Luis Garcia-Gancedo, et al.
JMIR Mhealth and Uhealth|December 21, 2019
Objectively Monitoring Amyotrophic Lateral Sclerosis Patient Symptoms During Clinical Trials With Sensors: Observational StudyLuis Garcia-Gancedo, Madeline L Kelly, Arseniy Lavrov, et al.
Pageof 1