39
勝
サイエンスパーク論文数
ジャーナル一覧
European Urology Oncology
医
IF = 9.3
NeuroToxicology
医
IF = 3.9
Fuel
化
IF = 7.4
Briefings in Bioinformatics
医
IF = 6.8
Microbial Risk Analysis
医
IF = 4
Psychiatry Research
医
IF = 3.9
Clinical Nutrition ESPEN
医
IF = 2.6
Cancers
医
IF = 4.4
Journal of Dairy Science
化
IF = 4.4
Annals of Epidemiology
医
IF = 3
The Journal of Pain
医
IF = 4
Veterinary Microbiology
医
IF = 2.7
Canadian Journal of Cardiology
医
IF = 5.3
Clinical Oncology
医
IF = 3
The Journal of Thoracic and Cardiovascular Surgery
医
IF = 4.4
Clinical Lung Cancer
医
IF = 3.3
Computer Methods and Programs in Biomedicine
医
IF = 4.8
Ultrasound in Medicine & Biology
医
IF = 2.6
European Neuropsychopharmacology
医
IF = 6.7
Radiotherapy and Oncology
医
IF = 5.3
Neuroscience
医
IF = 3.9
Environmental Modelling & Software
環
IF = 4.6
Journal of Clinical Lipidology
医
IF = 4.6
Ultrasound in Medicine & Biology
医
IF = 2.6
Journal of Cardiothoracic and Vascular Anesthesia
医
IF = 2.1
Food Chemistry
化
IF = 9.8
Environmental Research
環
IF = 7.7
European Journal of Cancer
医
IF = 7.1
Journal of Affective Disorders
医
IF = 4.9
Academic Radiology
医
IF = 3.1
Building and Environment
建
IF = 7.6
International Journal of Gynecological Cancer
医
IF = 4.7
European Journal of Radiology
医
IF = 3.3
Australian Critical Care
医
IF = 2.7
Computers in Biology and Medicine
医
IF = 6.3
Scripta Materialia
化
IF = 5.6
Science of The Total Environment
環
IF = 8
Journal of Hazardous Materials
環
IF = 11.3
European Journal of Surgical Oncology
医
IF = 2.9
論文リスト
| No. | Title | Authors | Journal | Year | DOI |
|---|---|---|---|---|---|
| 40 | Re: Jurczok N, Dernbach G, Ebner B, et al. Multiregional immune profiling reveals prognostic patterns in bladder cancer. Eur Urol Oncol. In press. http://dx.doi.org/10.1016/j.euo.2025.12.006 | Yoshida Kiyo, Oka Souichi, Takefuji Yoshiyasu | European Urology Oncology | 2026 | 10.1016/j.euo.2026.03.027 |
| 39 | Reconsidering principal component analysis in neurodevelopmental studies: A call for advanced frameworks | Oka Souichi, Ono Ryota, Takefuji Yoshiyasu | NeuroToxicology | 2026 | 10.1016/j.neuro.2026.103456 |
| 38 | Limits of SHAP feature importance in XGBoost–SOL Surrogates for catalytic Cracking: Correlation-Driven Bias, stability Diagnostics, and the Need for unsupervised validation | Ghale Suyam, Oka Souichi, Takefuji Yoshiyasu | Fuel | 2026 | 10.1016/j.fuel.2026.139411 |
| 37 | Addressing biases and limitations in feature attribution for circRNA modification profiling | Oka Souichi, Takemura Kota, Takefuji Yoshiyasu | Briefings in Bioinformatics | 2026 | 10.1093/bib/bbag168 |
| 36 | Interpreting genomics-driven microbial criteria: Toward robust and transparent risk models | Oka Souichi, Yoshida Kiyo, Takefuji Yoshiyasu | Microbial Risk Analysis | 2026 | 10.1016/j.mran.2026.100372 |
| 35 | Breaking the spline: Why distributed lag non-linear models miss thresholds in environmental psychiatry | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Psychiatry Research | 2026 | doi.org/10.1016/j.psychres.2026.117104 |
| 33 | Interpreting IDDSI-linked nutrient patterns: From correlations to compositional modules | Oka Souichi, Yoshida Kiyo, Takefuji Yoshiyasu | Clinical Nutrition ESPEN | 2026 | 10.1016/j.clnesp.2026.102982 |
| 32 | Revisiting AI Interpretability in Precision Oncology: Why Predictive Accuracy Does Not Ensure Stable Feature Importance | Oka Souichi, Takefuji Yoshiyasu | Cancers | 2026 | 10.3390/cancers18040593 |
| 31 | Letter to the Editor: Addressing the limitations of principal component analysis in dairy flavor research | Oka Souichi, Inoue Nobuko, Takefuji Yoshiyasu | Journal of Dairy Science | 2026 | 10.3168/jds.2025-27656 |
| 30 | Towards reliable feature interpretation in machine learning-based longevity prediction | Oka Souichi, Takahashi Yoshiki, Takefuji Yoshiyasu | Annals of Epidemiology | 2026 | 10.1016/j.annepidem.2026.01.005 |
| 29 | Beyond linear assumptions: Advancing lipidomic analysis in localized provoked vulvodynia | Oka Souichi, Yoshida Kiyo, Takefuji Yoshiyasu | The Journal of Pain | 2026 | 10.1016/j.jpain.2025.106179 |
| 28 | From bias to reliable insight: Rethinking feature importance in microbiome analytics | Oka Souichi, Yoshida Kiyo, Takefuji Yoshiyasu | Veterinary Microbiology | 2026 | 10.1016/j.vetmic.2025.110838 |
| 27 | Feature Importance Bias: Addressing Interpretability Issues in Tree-Based Acute Myocardial Infarction Risk Models | Oka Souichi, Takemura Kota, Takefuji Yoshiyasu | Canadian Journal of Cardiology | 2026 | 10.1016/j.cjca.2025.11.032 |
| 26 | Beyond Parametric Boundaries: Rethinking the Distributed Lag Nonlinear Model in Meteorological Modelling for Oncology Emergencies | Oka S., Yoshida K., Takefuji Y. | Clinical Oncology | 2026 | 10.1016/j.clon.2025.103970 |
| 25 | Beyond linear and parametric assumptions: A call for robust models in donor extracellular vesicles transcriptomics | Oka Souichi, Yoshida Kiyo, Takefuji Yoshiyasu | The Journal of Thoracic and Cardiovascular Surgery | 2026 | 10.1016/j.jtcvs.2025.09.041 |
| 24 | Revisiting AI Model Interpretability in Lung Cancer Screening: Challenges in Balancing Predictive Performance and Reliability | Oka Souichi, Takefuji Yoshiyasu | Clinical Lung Cancer | 2026 | 10.1016/j.cllc.2025.09.005 |
| 23 | Beyond predictive accuracy: Statistical validation of feature importance in biomedical machine learning | Oka Souichi, Inoue Nobuko, Takefuji Yoshiyasu | Computer Methods and Programs in Biomedicine | 2025 | 10.1016/j.cmpb.2025.109085 |
| 22 | Towards Reliable Feature Importance in Hashimoto's Thyroiditis Prediction: Reconstructing Machine Learning Frameworks | Oka Souichi, Takefuji Yoshiyasu | Ultrasound in Medicine & Biology | 2026 | 10.1016/j.ultrasmedbio.2025.09.008 |
| 21 | A call for more robust and interpretable models in predicting treatment-resistant depression | Oka Souichi, Takemura Kota, Takefuji Yoshiyasu | European Neuropsychopharmacology | 2025 | 10.1016/j.euroneuro.2025.09.012 |
| 20 | Towards reliable feature interpretation in machine learning-based acute diarrhoea toxicity assessment | Oka Souichi, Takahashi Yoshiki, Takefuji Yoshiyasu | Radiotherapy and Oncology | 2025 | 10.1016/j.radonc.2025.111140 |
| 19 | Reassessing PCA-based characterization of spiral ganglion neuron cell lines | Oka Souichi, Ono Ryota, Takefuji Yoshiyasu | Neuroscience | 2025 | 10.1016/j.neuroscience.2025.09.036 |
| 18 | Pitfalls of XAI interpretation in environmental modeling: A warning on model bias in air quality data analysis | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Environmental Modelling & Software | 2025 | 10.1016/j.envsoft.2025.106700 |
| 17 | Enhancing lipoprotein(a) association studies: A complementary approach to principal component analysis | Oka Souichi, Inoue Nobuko, Takefuji Yoshiyasu | Journal of Clinical Lipidology | 2025 | 10.1016/j.jacl.2025.08.021 |
| 16 | Methodological Concerns in Radiomics: Addressing Bias in LASSO and SHAP for Thyroid Tumor Analysis | Iwata Naoki, Oka Souichi, Takefuji Yoshiyasu | Ultrasound in Medicine & Biology | 2025 | 10.1016/j.ultrasmedbio.2025.08.016 |
| 15 | Clinical Machine Learning Pitfalls: Reliability of Feature Importance in Prediction of Continuous Renal Replacement Therapy in Acute Type A Aortic Dissection Assessment | Oka Souichi, Takefuji Yoshiyasu | Journal of Cardiothoracic and Vascular Anesthesia | 2025 | 10.1053/j.jvca.2025.08.035 |
| 14 | Addressing Bias in machine learning feature importance for food quality assessment | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Food Chemistry | 2025 | 10.1016/j.foodchem.2025.146171 |
| 13 | Beyond model-specific biases: An explainable multifaceted approach for robust PM10 source apportionment | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Environmental Research | 2025 | 10.1016/j.envres.2025.122656 |
| 12 | Letter Re: Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | European Journal of Cancer | 2025 | 10.1016/j.ejca.2025.115733 |
| 11 | Reassessing lipid-mood disorder associations: The limitations of PCA for nonlinear patterns | Ogawa Soki, Oka Souichi, Takefuji Yoshiyasu | Journal of Affective Disorders | 2025 | 10.1016/j.jad.2025.120024 |
| 10 | Robust Feature Attribution in Radiomics: A Call for Multi-faceted Methodologies | Oka Souichi, Takefuji Yoshiyasu | Academic Radiology | 2025 | 10.1016/j.acra.2025.07.048 |
| 9 | Feature importance in building machine learning: Beyond model-dependent interpretations | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Building and Environment | 2025 | 10.1016/j.buildenv.2025.113493 |
| 8 | Correspondence on “Large-scale analysis to identify risk factors for ovarian cancer” by Madakkatel et al | Oka Souichi, Takefuji Yoshiyasu | International Journal of Gynecological Cancer | 2025 | 10.1016/j.ijgc.2025.102000 |
| 7 | Complementing interpretable machine learning with synergistic analytical strategies for thyroid cancer recurrence prediction | Oka Souichi, Takefuji Yoshiyasu | European Journal of Radiology | 2025 | 10.1016/j.ejrad.2025.112308 |
| 6 | Re-evaluating structural equation modelling in nursing research: Insights from compassion fatigue and empowerment in Chinese intensive care units | Egawa Mana, Oka Souichi, Takefuji Yoshiyasu | Australian Critical Care | 2025 | 10.1016/j.aucc.2025.101292 |
| 5 | Letter to the Editor: Complementary statistical approaches for interpreting machine learning feature importance in osteoporosis risk | Oka Souichi, Yamazaki Takuma, Takefuji Yoshiyasu | Computers in Biology and Medicine | 2025 | 10.1016/j.compbiomed.2025.110710 |
| 4 | Comments on "Toward prediction and insight of porosity formation in laser welding: A physics-informed deep learning framework" | Oka Souichi, Takefuji Yoshiyasu | Scripta Materialia | 2025 | 10.1016/j.scriptamat.2025.116857 |
| 3 | 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 175091 | Oka Souichi, Takefuji Yoshiyasu | Science of The Total Environment | 2025 | 10.1016/j.scitotenv.2025.179714 |
| 2 | Comments on "Dialogue between algorithms and soil: Machine learning unravels the mystery of phthalates pollution in soil" by Pan et al. (2025) | Oka Souichi, Takefuji Yoshiyasu | Journal of Hazardous Materials | 2025 | 10.1016/j.jhazmat.2025.138366 |
| 1 | Comment on "Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection" | Oka Souichi, Takefuji Yoshiyasu | European Journal of Surgical Oncology | 2025 | 10.1016/j.ejso.2025.110025 |