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Souichi Oka

Showing results (1-10 of 19) with videos related to

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European Journal of Radiology|July 15, 2025
Complementing interpretable machine learning with synergistic analytical strategies for thyroid cancer recurrence predictionSouichi Oka, Yoshiyasu Takefuji
Journal of Hazardous Materials|April 24, 2025
Comments on "Dialogue between algorithms and soil: Machine learning unravels the mystery of phthalates pollution in soil" by Pan et al. (2025)Souichi Oka, Yoshiyasu Takefuji
The Science of the Total Environment|May 24, 2025
Letter to the Editor regarding "Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints" by Song et al. (2024), Sci. Total Environ. 950 175091Souichi Oka, Yoshiyasu Takefuji
Cancers|February 27, 2026
Revisiting AI Interpretability in Precision Oncology: Why Predictive Accuracy Does Not Ensure Stable Feature ImportanceSouichi Oka, Yoshiyasu Takefuji
Environmental Research|August 24, 2025
Beyond model-specific biases: An explainable multifaceted approach for robust PM<sub>10</sub> source apportionmentSouichi Oka, Takuma Yamazaki, Yoshiyasu Takefuji
Food Chemistry|September 3, 2025
Addressing Bias in machine learning feature importance for food quality assessmentSouichi Oka, Takuma Yamazaki, Yoshiyasu Takefuji
Briefings in Bioinformatics|April 9, 2026
Addressing biases and limitations in feature attribution for circRNA modification profilingSouichi Oka, Kota Takemura, Yoshiyasu Takefuji
Neurotoxicology|April 22, 2026
Reconsidering Principal Component Analysis in Neurodevelopmental Studies: A Call for Advanced FrameworksSouichi Oka, Ryota Ono, Yoshiyasu Takefuji
Journal of Affective Disorders|August 7, 2025
Reassessing lipid-mood disorder associations: The limitations of PCA for nonlinear patternsSoki Ogawa, Souichi Oka, Yoshiyasu Takefuji
Computer Methods and Programs in Biomedicine|September 28, 2025
Beyond predictive accuracy: Statistical validation of feature importance in biomedical machine learningSouichi Oka, Nobuko Inoue, Yoshiyasu Takefuji
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
European Journal of Radiology|July 15, 2025
Complementing interpretable machine learning with synergistic analytical strategies for thyroid cancer recurrence predictionSouichi Oka, Yoshiyasu Takefuji
Journal of Hazardous Materials|April 24, 2025
Comments on "Dialogue between algorithms and soil: Machine learning unravels the mystery of phthalates pollution in soil" by Pan et al. (2025)Souichi Oka, Yoshiyasu Takefuji
The Science of the Total Environment|May 24, 2025
Letter to the Editor regarding "Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints" by Song et al. (2024), Sci. Total Environ. 950 175091Souichi Oka, Yoshiyasu Takefuji
Cancers|February 27, 2026
Revisiting AI Interpretability in Precision Oncology: Why Predictive Accuracy Does Not Ensure Stable Feature ImportanceSouichi Oka, Yoshiyasu Takefuji
Environmental Research|August 24, 2025
Beyond model-specific biases: An explainable multifaceted approach for robust PM<sub>10</sub> source apportionmentSouichi Oka, Takuma Yamazaki, Yoshiyasu Takefuji
Food Chemistry|September 3, 2025
Addressing Bias in machine learning feature importance for food quality assessmentSouichi Oka, Takuma Yamazaki, Yoshiyasu Takefuji
Briefings in Bioinformatics|April 9, 2026
Addressing biases and limitations in feature attribution for circRNA modification profilingSouichi Oka, Kota Takemura, Yoshiyasu Takefuji
Neurotoxicology|April 22, 2026
Reconsidering Principal Component Analysis in Neurodevelopmental Studies: A Call for Advanced FrameworksSouichi Oka, Ryota Ono, Yoshiyasu Takefuji
Journal of Affective Disorders|August 7, 2025
Reassessing lipid-mood disorder associations: The limitations of PCA for nonlinear patternsSoki Ogawa, Souichi Oka, Yoshiyasu Takefuji
Computer Methods and Programs in Biomedicine|September 28, 2025
Beyond predictive accuracy: Statistical validation of feature importance in biomedical machine learningSouichi Oka, Nobuko Inoue, Yoshiyasu Takefuji
Pageof 2