Musashino University

Reevaluating feature importance in machine learning: concerns regarding SHAP interpretations in the context of the EU artificial intelligence act

Yoshiyasu Takefuji

2025 · 13 Zit.

Why AI image generators cannot afford to be blind to racial bias

Muhammad Arif, Yoshiyasu Takefuji

2025 · 2 Zit.

Comment on "Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection"

Souichi Oka, Yoshiyasu Takefuji

2025 · 2 Zit.

Addressing bias in feature importances derived from XGBoost. Comment on Br J Anaesth 2024;133:351–9

Yoshiyasu Takefuji

2025 · 2 Zit.

Generative AI for diabetologists: a concise tutorial on dataset analysis

Yoshiyasu Takefuji

2024 · 2 Zit.

Letter Re: Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences

Souichi Oka, Takuma Yamazaki, Yoshiyasu Takefuji

2025 · 1 Zit.

Leveraging human-AI collaboration to visualize age-related diabetes features using dataset

Yoshiyasu Takefuji

2024 · 1 Zit.

Preliminary study of a fashion recommendation system using ChatGPT: Possibilities, limitations, and future

Risa Aihara, Yusuke Hoshino

2024 · 0 Zit.

Towards reliable feature interpretation in machine learning-based longevity prediction

Souichi Oka, Yoshiki Takahashi, Yoshiyasu Takefuji

2026 · 0 Zit.

Methodological Concerns in Radiomics: Addressing Bias in LASSO and SHAP for Thyroid Tumor Analysis

Naoki Iwata, Souichi Oka, Yoshiyasu Takefuji

2025 · 0 Zit.

Enhancing Inpatient Mortality Prognostication in Cirrhosis Patients Through Machine Learning Techniques

Yoshiyasu Takefuji

2026 · 0 Zit.