World's Best Scientists 2026 revealed!
Yoichi Hayashi

Yoichi Hayashi

D-Index & Metrics

Computer Science

D-Index
37
Citations
11517
World Ranking
10469
National Ranking
156

Overview

Yoichi Hayashi is affiliated with Meiji University in Japan and has contributed extensively to the fields of computer science and medicine, with a specific focus on artificial intelligence and its applications. Their research spans multiple subfields including artificial intelligence, computer vision and pattern recognition, information systems, health informatics, and radiology, nuclear medicine, and imaging.

Their primary topics of work include:

  • Explainable Artificial Intelligence (XAI)
  • Artificial Intelligence in Healthcare and Education
  • Imbalanced Data Classification Techniques
  • AI in cancer detection
  • Data Mining Algorithms and Applications
  • Machine Learning in Healthcare
  • Financial Distress and Bankruptcy Prediction

Hayashi has published in several venues, notably:

  • Electronics
  • Journal of Artificial Intelligence and Soft Computing Research
  • The Journal of Physical Fitness and Sports Medicine
  • Information Fusion
  • arXiv (Cornell University)

Recent papers authored or coauthored by Hayashi include:

  • "Emerging Trends in Deep Learning for Credit Scoring: A Review" (2022) published in Electronics
  • "One-Dimensional Convolutional Neural Networks with Feature Selection for Highly Concise Rule Extraction from Credit Scoring Datasets with Heterogeneous Attributes" (2020) published in Electronics

Other recent papers in related collaborations feature work on explainable AI and user identification methods, such as:

  • "Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions" (2024) published in Information Fusion
  • "Browser Fingerprint Coding Methods Increasing the Effectiveness of User Identification in the Web Traffic" (2020) published in Journal of Artificial Intelligence and Soft Computing Research

Hayashi frequently collaborates with the following researchers:

  • Shun Wakatabe
  • Luca Longo
  • Mario Brčić
  • Federico Cabitza
  • Jaesik Choi

Best Publications

  • Fuzzy hierarchical analysis

    J.J. Buckley;T. Feuring;Y. Hayashi

  • Neuro-fuzzy rule generation: survey in soft computing framework

    S. Mitra;Y. Hayashi

  • Fuzzy neural networks: a survey

    James J. Buckley;Yoichi Hayashi

  • Fuzzy neural network with fuzzy signals and weights

    Yoichi Hayashi;James J. Buckley;Ernest Czogala

  • Fuzzy hierarchical analysis revisited

    James J. Buckley;Thomas Feuring;Yoichi Hayashi

  • Neural expert system using fuzzy teaching input and its application to medical diagnosis

    Yoichi Hayashi

  • Can fuzzy neural nets approximate continuous fuzzy functions

    James J. Buckley;Yoichi Hayashi

  • Neural nets for fuzzy systems

    James J. Buckley;Yoichi Hayashi

  • Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system

    Karl Boegl;Klaus-Peter Adlassnig;Yoichi Hayashi;Thomas E. Rothenfluh

  • Fuzzy genetic algorithm and applications

    James J. Buckley;Yoichi Hayashi

  • Bioinformatics with soft computing

    S. Mitra;Y. Hayashi

  • Fuzzy input-output controllers are universal approximators

    James J. Buckley;Yoichi Hayashi

  • On the equivalence of neural nets and fuzzy expert systems

    James J. Buckley;Yoichi Hayashi;Ernest Czogała

  • A novel control of a current source active filter for AC power system harmonic compensation

    Y. Hayashi;N. Sato;K. Takahashi

  • Genetic learning algorithms for fuzzy neural nets

    P.V. Krishnamraju;J.J. Buckley;K.D. Reilly;Y. Hayashi

  • A new approach to calculating core losses in the SRM

    Y. Hayashi;T.J.E. Miller

  • Rule extraction using Recursive-Rule extraction algorithm with J48graft combined with sampling selection techniques for the diagnosis of type 2 diabetes mellitus in the Pima Indian dataset

    Yoichi Hayashi;Shonosuke Yukita

  • Characterization of symbolic rules embedded in deep DIMLP networks : a challenge to transparency of deep learning

    Guido Bologna;Yoichi Hayashi

  • A comparison between two neural network rule extraction techniques for the diagnosis of hepatobiliary disorders

    Yoichi Hayashi;Rudy Setiono;Katsumi Yoshida

  • Fuzzy neural controller

    Y. Hayashi;E. Czogala;J.J. Buckley

  • A NEURAL EXPERT SYSTEM WITH AUTOMATED EXTRACTION OF FUZZY IF-THEN RULES

    Yoichi Hayashi

Frequent Co-Authors

James J. Buckley
James J. Buckley University of Alabama at Birmingham
Rudy Setiono
Rudy Setiono National University of Singapore
Krzysztof Cpałka
Krzysztof Cpałka Częstochowa University of Technology
Sushmita Mitra
Sushmita Mitra Indian Statistical Institute
Włodzisław Duch
Włodzisław Duch Nicolaus Copernicus University
James M. Keller
James M. Keller University of Missouri
Nikhil R. Pal
Nikhil R. Pal Indian Statistical Institute

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