Hayashi Yoichi 林陽一

… Alternative Names

林陽一ハヤシヨウイチ

HAYASHI Yoichi 林陽一

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Researcher Number	20189666
Other IDs	https://orcid.org/0000-0002-8359-374X
Affiliation (Current)	2025: 明治大学, 理工学部, 専任教授
Affiliation (based on the past Project Information) *help	2018 – 2024: 明治大学, 理工学部, 専任教授 2000: 明治大学, 理工学部, 教授 1989: Assistant Professor, Department of Information Science, School of Engineering, I, 講師 1987: 茨城大学, 工学部, 専任講師
Review Section/Research Field	Principal Investigator Basic Section 61040:Soft computing-related / Biological Sciences Except Principal Investigator Basic Section 55060:Emergency medicine-related
Keywords	Principal Investigator ルール抽出 / 説明可能AI / ルールベース / 機械学習 / XGBoost / 画像特徴抽出 / 透明化 / 高精度分類器 / アンサンブル学習 / 予測モデル … More / 病理画像 / ルール表現 / 放射線画像 / 構造化データ / 解釈可能性 / 透明性 / 分かりやすさ / 名義変数 / 説明能力 / 解釈性 / ブラックボックス / 深層学習 / 医用画像 / ディープラーニング / 知識発見 / ニューラルネットワーク / データマイニング … More Except Principal Investigator Vector quantization / Hypercube architecute / Fuzzy reasoning / Computer architecture / Natural Language Processing / Programming Languages / Algorithms / ルール抽出技術 / 術後合併症 / 人工呼吸療法 / 術後肺合併症 / 心臓血管外科手術 / 合併症 / 心疾患 / AI / アルゴリズム / 心臓外科 / 集中治療 / 人工知能 / Neuro-computing / Neuroーcomputing Less

A study on rule-based approach to the black box nature of XGBoostPrincipal Investigator
- Principal Investigator
  
  林陽一
- Project Period (FY)
  2024 – 2026
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 61040:Soft computing-related
- Research Institution
  Meiji University
Development of algorithm for predicting risk of pulmonary complications after cardiac surgery using artificial intelligence rule extraction technology
- Principal Investigator
  
  Ichiba.shingo Shingo
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 55060:Emergency medicine-related
- Research Institution
  Tokyo Women's Medical University
Study on the rule representations and transparency of feature extracted images obtained by deep learningPrincipal Investigator
- Principal Investigator
  
  Hayashi Yoichi
- Project Period (FY)
  2018 – 2020
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 61040:Soft computing-related
- Research Institution
  Meiji University
ニューロデータマイニングによるゲノムデータベースからの知識発見Principal Investigator
- Principal Investigator
  
  林陽一
- Project Period (FY)
  2000 – 2001
- Research Category
  
  Grant-in-Aid for Scientific Research on Priority Areas (C)
- Review Section
  
  Biological Sciences
- Research Institution
  Meiji University
General Studies on High Level Techniques in Computer Software and Hardware
- Principal Investigator
  
  TAKAOKA Tadao
- Project Period (FY)
  1987 – 1989
- Research Category
  
  Grant-in-Aid for Overseas Scientific Survey.
- Research Institution
  Ibaraki University

All 2022 2020 2019 2018

All Journal Article Presentation

[Journal Article] Does deep learning work well for categorical datasets with mainly nominal attributes?2020
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Electronics
  
  Volume: 9 Issue: 11 Pages: 1966-1966
- DOI
  10.3390/electronics9111966
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Rough Support Vector Machine for Classification with Interval and Incomplete Data2020
- Author(s)
  1.Nowicki Robert K, Grzanek K, Yoichi Hayashi
- Journal Title
  
  Journal of Artificial Intelligence and Soft Computing Research
  
  Volume: 10 Pages: 47-56
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Browser Fingerprint Coding Methods Increasing The Effectiveness of User Identification in The Web Traffic2020
- Author(s)
  Marcin Gabryel, Konrad Grzanek, Yoichi Hayashi
- Journal Title
  
  Journal of Artificial Intelligence and Soft Computing Research
  
  Volume: 10 Issue: 4 Pages: 243-253
- DOI
  10.2478/jaiscr-2020-0016
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] New unified insights on deep learning in radiological and pathological images: beyond quantitative performances to qualitative interpretation2020
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Informatics in Medicine Unlocked
  
  Volume: 19 Pages: 100329-100329
- DOI
  10.1016/j.imu.2020.100329
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Black Box Nature of Deep Learning for: Digital Pathology Beyond Quantitative to Qualitative Algorithmic Performances2020
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Lecture Notes on Artificial Intelligence (LNAI)
  
  Volume: 12090 Pages: 95-101
- DOI
  10.1007/978-3-030-50402-1_6
- ISBN
  9783030504014, 9783030504021
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] One-dimensional convolutional neural networks with feature selection for highly concise rule extraction from credit scoring datasets with heterogeneous attributes2020
- Author(s)
  Yoichi Hayashi, Naoki Takano
- Journal Title
  
  Electronics
  
  Volume: 9 Issue: 8 Pages: 1318-1318
- DOI
  10.3390/electronics9081318
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Toward to transparency of deep learning in radiological imaging: Beyond quantitative to qualitative AI2019
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Journal of Medical Artificial Intelligence
  
  Volume: 2 Pages: 19-19
- DOI
  10.21037/jmai.2019.09.06
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] The right direction to be needed to develop a white-box deep learning in radiology, pathology, and ophthalmology: A short review2019
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Frontiers in Robotics and AI
  
  Volume: 6
- DOI
  10.3389/frobt.2019.00024
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Artificial intelligence-based rule extraction approach to derive the upper limit of hemoglobin during anemia treatment in patients with predialysis chronic kidney disease2019
- Author(s)
  Yoichi Hayashi, Kei Nakajima, Keisuke Nakajima
- Journal Title
  
  Informatics in Medicine Unlocked
  
  Volume: 17 Pages: 100262-100262
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Detection of lower albuminuria levels and early development of diabetic kidney disease using an artificial intelligence-based rule extraction approach2019
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Diagnostics
  
  Volume: 9 Pages: 33-33
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] A Rule Extraction Study from SVM on Sentiment Analysis, Big Data and Cognitive Computing2018
- Author(s)
  6.Guido Bologna, Yoichi Hayashi
- Journal Title
  
  Big Data and Cognitive Computing
  
  Volume: 2018 Issue: 1 Pages: 6-6
- DOI
  10.3390/bdcc2010006
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Non-invasive prediction of non-alcoholic steatohepatitis in Japanese patients with morbid obesity by artificial intelligence using rule extraction technology.2018
- Author(s)
  Uehara D, Hayashi Y, Seki Y, Kakizaki S, Horiguchi N, Tojima H, Yamazaki Y, Sato K, Yasuda K, Yamada M, Uraoka T, Kasama K.
- Journal Title
  
  World J Hepatol.
  
  Volume: Dec 27;10(12) Issue: 12 Pages: 934-943
- DOI
  10.4254/wjh.v10.i12.934
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-16K09339, KAKENHI-PROJECT-18K11481, KAKENHI-PROJECT-16K01850
[Journal Article] Optimality and convergence for convex ensemble learning with sparsity and diversity based on fixed point optimization2018
- Author(s)
  Yoichi Hayashi and Hideaki Iiduka
- Journal Title
  
  Neurocomputing
  
  Volume: 273 Pages: 367-372
- DOI
  10.1016/j.neucom.2017.07.046
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-15K04763, KAKENHI-PROJECT-18K11481
[Journal Article] High accuracy-priority rule extraction for reconciling accuracy an interpretability in credit scoring2018
- Author(s)
  Yoichi Hayashi, Tatsuhiro Oisi
- Journal Title
  
  New Generation Computing
  
  Volume: 36 Issue: 4 Pages: 393-418
- DOI
  10.1007/s00354-018-0043-5
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] A comparison study on rule extraction from neural network ensembles, Boosted shallow trees and SVMs2018
- Author(s)
  Guido Bologna, Yoichi Hayashi
- Journal Title
  
  Applied Computional Intelligence and Soft Computing
  
  Volume: 2018 Pages: 1-20
- DOI
  10.1155/2018/4084850
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K11481
[Journal Article] Use of deep belief network for high-level abstraction small data sets using artificial intelligence with rule extraction2018
- Author(s)
  Yoichi Hayashi
- Journal Title
  
  Neural Computation
  
  Volume: 30 Issue: 12 Pages: 3309-3326
- DOI
  10.1162/neco_a_01139
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-18K11481
[Presentation] 腹臥位中の集中治療　当院におけるVV-ECMO下の腹臥位管理法2022
- Author(s)
  工藤弦, 堀部達也, 加島広太, 菊地剛, 志真奈緒子, 青山要平, 野村岳志, 市場晋吾, 若林秀隆
- Organizer
  日本集中治療医学会
- Data Source
  KAKENHI-PROJECT-21K09084

1. TAKAOKA Tadao (00007824)

# of Collaborated Projects: 1 results

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2. TAMAKI Hisao (20111354)

# of Collaborated Projects: 1 results

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3. MATSUYAMA Yasuo (60125804)

# of Collaborated Projects: 1 results

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4. Ichiba.shingo Shingo (30284102)

# of Collaborated Projects: 1 results

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5. 野村岳志 (10243445)

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6. 新浪博 (30241079)

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7. 佐藤暢夫 (80439869)

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8. 清野雄介 (90366352)

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9. PRADIP Dey

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10. KEVIN D. Rei

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11. DEY Pradip

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12. REILLY Kevin D.

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13. BARRETT R.Br

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14. JOSEPH Fonta

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15. KEVIN D.Reil

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16. WARREN T.Jon

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17. 滑川英世

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18. IIDUKA Hideaki

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19. 柿崎暁

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20. 堀口昇男

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21. 山田英二郎

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Hayashi Yoichi 林 陽一

林 陽一 ハヤシ ヨウイチ

HAYASHI Yoichi 林 陽一

Research Projects

Research Products

Co-Researchers

A study on rule-based approach to the black box nature of XGBoostPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of algorithm for predicting risk of pulmonary complications after cardiac surgery using artificial intelligence rule extraction technology

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Study on the rule representations and transparency of feature extracted images obtained by deep learningPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

ニューロデータマイニングによるゲノムデータベースからの知識発見Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

General Studies on High Level Techniques in Computer Software and Hardware

Principal Investigator

Project Period (FY)

Research Category

Research Institution

[Journal Article] Does deep learning work well for categorical datasets with mainly nominal attributes?2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Rough Support Vector Machine for Classification with Interval and Incomplete Data2020

Author(s)

Journal Title

Data Source

[Journal Article] Browser Fingerprint Coding Methods Increasing The Effectiveness of User Identification in The Web Traffic2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] New unified insights on deep learning in radiological and pathological images: beyond quantitative performances to qualitative interpretation2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Black Box Nature of Deep Learning for: Digital Pathology Beyond Quantitative to Qualitative Algorithmic Performances2020

Author(s)

Journal Title

DOI

ISBN

Data Source

[Journal Article] One-dimensional convolutional neural networks with feature selection for highly concise rule extraction from credit scoring datasets with heterogeneous attributes2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Toward to transparency of deep learning in radiological imaging: Beyond quantitative to qualitative AI2019

Author(s)

Journal Title

DOI

Data Source

[Journal Article] The right direction to be needed to develop a white-box deep learning in radiology, pathology, and ophthalmology: A short review2019

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Artificial intelligence-based rule extraction approach to derive the upper limit of hemoglobin during anemia treatment in patients with predialysis chronic kidney disease2019

Author(s)

Journal Title

Data Source

[Journal Article] Detection of lower albuminuria levels and early development of diabetic kidney disease using an artificial intelligence-based rule extraction approach2019

Hayashi Yoichi 林陽一

林陽一ハヤシヨウイチ

HAYASHI Yoichi 林陽一

[Presentation] 腹臥位中の集中治療　当院におけるVV-ECMO下の腹臥位管理法2022