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Yoshiyuki Kobayashi

Assistant professor

Hoshi University

Japan

Research Interests

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Professors in Japan Professors in Food Science Food Science professors in Japan

About

Yoshiyuki Kobayashi is an Assistant Professor at Hoshi University in Japan. His research primarily focuses on public health, entrepreneurship education, and advanced analytical methods in biochemistry and environmental science. He has authored recent articles investigating HPV vaccination attitudes, corporate entrepreneurship, and the application of machine learning in predicting soil adsorption coefficients.

Articles (11)

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2026

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2021

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2020

Collaborators (2)

Shintaro Sengoku

Professor

Tokyo Institute of Technology

JAPAN

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yeongjoo lim

Ritsumeikan University

JAPAN

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Yoshiyuki Kobayashi

Research Interests

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Articles (11)

Comprehensive Analysis of Food Allergy Research Trends via Large Language Model–Assisted Text Mining (1980–2024)

Effects of passive information dissemination on human papillomavirus vaccination attitudes and knowledge among pharmacy visitors: A cluster randomized controlled trial

Does the Intuition of Top Managers Influence Corporate Entrepreneurship?

Mass spectrometry-based methods for biofluid biomarkers for progressive diseases: amyloid peptides and dystrophins

Entrepreneurial Intention Among Engineering Students: The Moderating Role of Entrepreneurship Education in Japan

Evolving Research and Development Landscape for Rare Diseases: Growing Concerns Over Orphan Drug Lag in Japan

Uncovering new psychoactive substances research trends using large language model-assisted text mining (LATeM)

Food Derived Biostimulants Technology Revealed and Retrieved by Natural Language Processing

The Influence of Food Intake and Blood Glucose on Postprandial Sleepiness and Work Productivity: A Scoping Review

Quantitative structure–property relationships for the calculation of the soil adsorption coefficient using machine learning algorithms with calculated chemical properties from open-source software

Prediction of Soil Adsorption Coefficient in Pesticides Using Physicochemical Properties and Molecular Descriptors by Machine Learning Models

Collaborators (2)

Shintaro Sengoku

yeongjoo lim

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