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AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science
|
June 23, 2023
Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notes
Claudio Fanconi, Marieke van Buchem, Tina Hernandez-Boussard
Ebiomedicine
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June 3, 2023
A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization
Claudio Fanconi, Anne de Hond, Dylan Peterson, et al.
Journal of Nephrology
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March 6, 2023
Correction to: Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
Francesco Sanmarchi, Claudio Fanconi, Davide Golinelli, et al.
Journal of Nephrology
|
February 14, 2023
Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
Francesco Sanmarchi, Claudio Fanconi, Davide Golinelli, et al.
Diagnostic and Prognostic Research
|
May 5, 2025
A scoping review of machine learning models to predict risk of falls in elders, without using sensor data
Angelo Capodici, Claudio Fanconi, Catherine Curtin, et al.
Studies in Health Technology and Informatics
|
May 19, 2023
Predicting Depression Risk in Patients with Cancer Using Multimodal Data
Anne de Hond, Marieke van Buchem, Claudio Fanconi, et al.
JMIR Medical Informatics
|
January 18, 2024
Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study
Anne de Hond, Marieke van Buchem, Claudio Fanconi, et al.
Journal of the American Medical Informatics Association : JAMIA
|
July 17, 2024
Applying natural language processing to patient messages to identify depression concerns in cancer patients
Marieke M van Buchem, Anne A H de Hond, Claudio Fanconi, et al.
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Search research articles
Search
Showing results (1-10 of 8) with videos related to
Sort By:
Page
of 1
AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science
|
June 23, 2023
Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notes
Claudio Fanconi, Marieke van Buchem, Tina Hernandez-Boussard
Ebiomedicine
|
June 3, 2023
A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization
Claudio Fanconi, Anne de Hond, Dylan Peterson, et al.
Journal of Nephrology
|
March 6, 2023
Correction to: Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
Francesco Sanmarchi, Claudio Fanconi, Davide Golinelli, et al.
Journal of Nephrology
|
February 14, 2023
Predict, diagnose, and treat chronic kidney disease with machine learning: a systematic literature review
Francesco Sanmarchi, Claudio Fanconi, Davide Golinelli, et al.
Diagnostic and Prognostic Research
|
May 5, 2025
A scoping review of machine learning models to predict risk of falls in elders, without using sensor data
Angelo Capodici, Claudio Fanconi, Catherine Curtin, et al.
Studies in Health Technology and Informatics
|
May 19, 2023
Predicting Depression Risk in Patients with Cancer Using Multimodal Data
Anne de Hond, Marieke van Buchem, Claudio Fanconi, et al.
JMIR Medical Informatics
|
January 18, 2024
Predicting Depression Risk in Patients With Cancer Using Multimodal Data: Algorithm Development Study
Anne de Hond, Marieke van Buchem, Claudio Fanconi, et al.
Journal of the American Medical Informatics Association : JAMIA
|
July 17, 2024
Applying natural language processing to patient messages to identify depression concerns in cancer patients
Marieke M van Buchem, Anne A H de Hond, Claudio Fanconi, et al.
Page
of 1