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Samer Albahra

Showing results (11-20 of 23) with videos related to

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Frontiers in Oncology|February 27, 2023
Common statistical concepts in the supervised Machine Learning arenaHooman H Rashidi, Samer Albahra, Scott Robertson, et al.
Scientific Reports|September 10, 2021
Automated machine learning for endemic active tuberculosis prediction from multiplex serological dataHooman H Rashidi, Luke T Dang, Samer Albahra, et al.
Journal of Imaging Informatics in Medicine|April 2, 2026
Automated Clinical Information Extraction from Diagnostic and Nondiagnostic Radiology Reports Using Modern Language ModelsBenjamin G Mittman, Giana D'Aleo, Michael B Rothberg, et al.
Clinical Chemistry|December 30, 2021
Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases TestingNam K Tran, Samer Albahra, Larissa May, et al.
Transplantation|February 9, 2021
Automated En Masse Machine Learning Model Generation Shows Comparable Performance as Classic Regression Models for Predicting Delayed Graft Function in Renal AllograftsKuang-Yu Jen, Samer Albahra, Felicia Yen, et al.
Plos One|July 29, 2022
Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MSHooman H Rashidi, John Pepper, Taylor Howard, et al.
Seminars in Diagnostic Pathology|March 4, 2023
Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised conceptsSamer Albahra, Tom Gorbett, Scott Robertson, et al.
Scientific Reports|July 25, 2020
Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of conceptNam K Tran, Samer Albahra, Tam N Pham, et al.
Cerebrovascular Diseases Extra|March 17, 2025
Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept StudyBing Yu Chen, Fares Antaki, Marco Gonzalez, et al.
Journal of Pathology Informatics|February 9, 2022
Prediction of Tuberculosis Using an Automated Machine Learning Platform for Models Trained on Synthetic DataHooman H Rashidi, Imran H Khan, Luke T Dang, et al.
Pageof 3

Showing results (11-20 of 23) with videos related to

Sort By:
Pageof 3
Frontiers in Oncology|February 27, 2023
Common statistical concepts in the supervised Machine Learning arenaHooman H Rashidi, Samer Albahra, Scott Robertson, et al.
Scientific Reports|September 10, 2021
Automated machine learning for endemic active tuberculosis prediction from multiplex serological dataHooman H Rashidi, Luke T Dang, Samer Albahra, et al.
Journal of Imaging Informatics in Medicine|April 2, 2026
Automated Clinical Information Extraction from Diagnostic and Nondiagnostic Radiology Reports Using Modern Language ModelsBenjamin G Mittman, Giana D'Aleo, Michael B Rothberg, et al.
Clinical Chemistry|December 30, 2021
Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases TestingNam K Tran, Samer Albahra, Larissa May, et al.
Transplantation|February 9, 2021
Automated En Masse Machine Learning Model Generation Shows Comparable Performance as Classic Regression Models for Predicting Delayed Graft Function in Renal AllograftsKuang-Yu Jen, Samer Albahra, Felicia Yen, et al.
Plos One|July 29, 2022
Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MSHooman H Rashidi, John Pepper, Taylor Howard, et al.
Seminars in Diagnostic Pathology|March 4, 2023
Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised conceptsSamer Albahra, Tom Gorbett, Scott Robertson, et al.
Scientific Reports|July 25, 2020
Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of conceptNam K Tran, Samer Albahra, Tam N Pham, et al.
Cerebrovascular Diseases Extra|March 17, 2025
Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept StudyBing Yu Chen, Fares Antaki, Marco Gonzalez, et al.
Journal of Pathology Informatics|February 9, 2022
Prediction of Tuberculosis Using an Automated Machine Learning Platform for Models Trained on Synthetic DataHooman H Rashidi, Imran H Khan, Luke T Dang, et al.
Pageof 3