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Bioengineering (Basel, Switzerland)
|
February 27, 2026
Development and Evaluation of a Urinary Na/K Ratio Prediction Model: A Systematic Comparison from Attention-Based Deep Learning to Classical Ensemble Approaches
Emi Yuda, Itaru Kaneko, Daisuke Hirahara
Peerj. Computer Science
|
April 5, 2021
Effects of data count and image scaling on Deep Learning training
Daisuke Hirahara, Eichi Takaya, Taro Takahara, et al.
Abdominal Radiology (New York)
|
March 6, 2021
Application of a machine learning approach to characterization of liver function using <sup>99m</sup>Tc-GSA SPECT/CT
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
March 25, 2021
Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [<sup>18</sup>F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
May 16, 2023
Application of Machine Learning Analyses Using Clinical and [<sup>18</sup>F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer
Kodai Kawaji, Masatoyo Nakajo, Yoshiaki Shinden, et al.
European Radiology
|
February 24, 2022
Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, et al.
Japanese Journal of Comprehensive Rehabilitation Science
|
September 8, 2025
Development and Evaluation of a Virtual Reality-Based Teaching Material for Interprofessional Education: A Case Study on Swallowing Videofluorography
Shotaro Komaki, Shogo Baba, Yuuko Yotsumoto, et al.
Abdominal Radiology (New York)
|
November 25, 2021
Machine learning based evaluation of clinical and pretreatment <sup>18</sup>F-FDG-PET/CT radiomic features to predict prognosis of cervical cancer patients
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
July 21, 2022
The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [<sup>18</sup>F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer
Masatoyo Nakajo, Kodai Kawaji, Hiromi Nagano, et al.
Japanese Journal of Radiology
|
December 28, 2024
Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [<sup>18</sup>F]-FDG-PET-radiomic features
Masatoyo Nakajo, Daisuke Hirahara, Megumi Jinguji, et al.
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Search research articles
Search
Showing results (1-10 of 22) with videos related to
Sort By:
Page
of 3
Bioengineering (Basel, Switzerland)
|
February 27, 2026
Development and Evaluation of a Urinary Na/K Ratio Prediction Model: A Systematic Comparison from Attention-Based Deep Learning to Classical Ensemble Approaches
Emi Yuda, Itaru Kaneko, Daisuke Hirahara
Peerj. Computer Science
|
April 5, 2021
Effects of data count and image scaling on Deep Learning training
Daisuke Hirahara, Eichi Takaya, Taro Takahara, et al.
Abdominal Radiology (New York)
|
March 6, 2021
Application of a machine learning approach to characterization of liver function using <sup>99m</sup>Tc-GSA SPECT/CT
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
March 25, 2021
Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [<sup>18</sup>F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
May 16, 2023
Application of Machine Learning Analyses Using Clinical and [<sup>18</sup>F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer
Kodai Kawaji, Masatoyo Nakajo, Yoshiaki Shinden, et al.
European Radiology
|
February 24, 2022
Deep learning approach of diffusion-weighted imaging as an outcome predictor in laryngeal and hypopharyngeal cancer patients with radiotherapy-related curative treatment: a preliminary study
Hayato Tomita, Tatsuaki Kobayashi, Eichi Takaya, et al.
Japanese Journal of Comprehensive Rehabilitation Science
|
September 8, 2025
Development and Evaluation of a Virtual Reality-Based Teaching Material for Interprofessional Education: A Case Study on Swallowing Videofluorography
Shotaro Komaki, Shogo Baba, Yuuko Yotsumoto, et al.
Abdominal Radiology (New York)
|
November 25, 2021
Machine learning based evaluation of clinical and pretreatment <sup>18</sup>F-FDG-PET/CT radiomic features to predict prognosis of cervical cancer patients
Masatoyo Nakajo, Megumi Jinguji, Atsushi Tani, et al.
Molecular Imaging and Biology
|
July 21, 2022
The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [<sup>18</sup>F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer
Masatoyo Nakajo, Kodai Kawaji, Hiromi Nagano, et al.
Japanese Journal of Radiology
|
December 28, 2024
Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [<sup>18</sup>F]-FDG-PET-radiomic features
Masatoyo Nakajo, Daisuke Hirahara, Megumi Jinguji, et al.
Page
of 3