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Milad Rahimi

Showing results (1-10 of 14) with videos related to

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Technology in Cancer Research & Treatment|December 18, 2023
Oncological Applications of Quantum Machine LearningMilad Rahimi, Farkhondeh Asadi
BMC Cancer|April 13, 2023
Cervical cancer survival prediction by machine learning algorithms: a systematic reviewMilad Rahimi, Atieh Akbari, Farkhondeh Asadi, et al.
Cancer Reports (Hoboken, N.J.)|March 19, 2025
Comparing the Effectiveness of Artificial Intelligence Models in Predicting Ovarian Cancer Survival: A Systematic ReviewFarkhondeh Asadi, Milad Rahimi, Nahid Ramezanghorbani, et al.
Health Science Reports|October 2, 2024
The most efficient machine learning algorithms in stroke prediction: A systematic reviewFarkhondeh Asadi, Milad Rahimi, Amir Hossein Daeechini, et al.
Scientific Reports|May 19, 2026
Machine learning surrogate for the leaf PROSPECT-D model and its applications across plant speciesMilad Rahimi-Majd, Rudan Xu, Stefan Bauermeister, et al.
Basic and Clinical Neuroscience|October 15, 2024
Introducing a New Method for Studying the Effects of Movement Synchrony in Virtual RealityMilad Yekani, Mehdi Tehrani-Doost, Milad Rahimi, et al.
Plant, Cell & Environment|August 21, 2024
Nonlinear models based on leaf architecture traits explain the variability of mesophyll conductance across plant speciesMilad Rahimi-Majd, Alistair Leverett, Arne Neumann, et al.
Medical Journal of the Islamic Republic of Iran|June 9, 2025
Identification of Important Diagnostic Genes in the Uterine Using Bioinformatics and Machine LearningHossein Valizadeh Laktarashi, Milad Rahimi, Kimia Abrishamifar, et al.
Health Science Reports|March 5, 2026
Sensor-Equipped Digital Technologies for Monitoring and Detecting Depressive Disorders: A Systematic ReviewMilad Rahimi, Kimia Abrishamifar, Shadi Hazhir, et al.
International Journal of Biological Macromolecules|March 11, 2021
Ultrasonically developed silver/iota-carrageenan/cotton bionanocomposite as an efficient material for biomedical applicationsZoha Noralian, Mazeyar Parvinzadeh Gashti, Milad Rahimi Moghaddam, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Technology in Cancer Research & Treatment|December 18, 2023
Oncological Applications of Quantum Machine LearningMilad Rahimi, Farkhondeh Asadi
BMC Cancer|April 13, 2023
Cervical cancer survival prediction by machine learning algorithms: a systematic reviewMilad Rahimi, Atieh Akbari, Farkhondeh Asadi, et al.
Cancer Reports (Hoboken, N.J.)|March 19, 2025
Comparing the Effectiveness of Artificial Intelligence Models in Predicting Ovarian Cancer Survival: A Systematic ReviewFarkhondeh Asadi, Milad Rahimi, Nahid Ramezanghorbani, et al.
Health Science Reports|October 2, 2024
The most efficient machine learning algorithms in stroke prediction: A systematic reviewFarkhondeh Asadi, Milad Rahimi, Amir Hossein Daeechini, et al.
Scientific Reports|May 19, 2026
Machine learning surrogate for the leaf PROSPECT-D model and its applications across plant speciesMilad Rahimi-Majd, Rudan Xu, Stefan Bauermeister, et al.
Basic and Clinical Neuroscience|October 15, 2024
Introducing a New Method for Studying the Effects of Movement Synchrony in Virtual RealityMilad Yekani, Mehdi Tehrani-Doost, Milad Rahimi, et al.
Plant, Cell & Environment|August 21, 2024
Nonlinear models based on leaf architecture traits explain the variability of mesophyll conductance across plant speciesMilad Rahimi-Majd, Alistair Leverett, Arne Neumann, et al.
Medical Journal of the Islamic Republic of Iran|June 9, 2025
Identification of Important Diagnostic Genes in the Uterine Using Bioinformatics and Machine LearningHossein Valizadeh Laktarashi, Milad Rahimi, Kimia Abrishamifar, et al.
Health Science Reports|March 5, 2026
Sensor-Equipped Digital Technologies for Monitoring and Detecting Depressive Disorders: A Systematic ReviewMilad Rahimi, Kimia Abrishamifar, Shadi Hazhir, et al.
International Journal of Biological Macromolecules|March 11, 2021
Ultrasonically developed silver/iota-carrageenan/cotton bionanocomposite as an efficient material for biomedical applicationsZoha Noralian, Mazeyar Parvinzadeh Gashti, Milad Rahimi Moghaddam, et al.
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