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関連する概念動画

Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

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The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
778
Wind Turbine Machine Models01:24

Wind Turbine Machine Models

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In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
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Machines01:19

Machines

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
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Interpreting R Charts01:22

Interpreting R Charts

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
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関連する実験動画

Updated: Feb 2, 2026

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Acupoint determinationのための階層的かつ解釈可能な機械学習モデル

Hang Yang1, Ren Wu2, Mitsuru Nakata3

  • 1The Graduate School of East Asian Studies, Yamaguchi University, Yamaguchi-shi 753-8514 Yamaguchi, Japan.

Journal of integrative medicine
|January 31, 2026
PubMed
まとめ
この要約は機械生成です。

本研究では、鍼灸・艾治療（AMT）における個別化された経穴処方のための機械学習モデルを開発した。階層的かつ解釈可能なモデルは、治療効率と臨床的適用性を向上させる。

キーワード:
経穴処方鍼灸・艾治療階層的分類機械学習

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科学分野:

  • 統合医療
  • ヘルスケアにおける人工知能
  • 伝統中国医学

背景:

  • 鍼灸・艾治療（AMT）の効果は、個別化された治療戦略によって高めることができます。
  • 経穴処方のためのデータ駆動型モデルの開発は、AMTの進歩にとって重要です。

研究 の 目的:

  • 患者の症状に基づいた個別化された経穴処方のための機械学習モデルを開発すること。
  • インテリジェントシステムを通じて鍼灸・艾治療（AMT）の効率と有効性を向上させること。

主な方法:

  • 症状ベースの経穴予測のために、階層的注意機構付きリカレントニューラルネットワーク（HARNN）を採用しました。
  • データの前処理と拡張を利用して、堅牢な機械学習データベースを構築しました。
  • モデルの解釈可能性と臨床的検証のために、局所解釈可能モデル非依存型説明（LIME）を適用しました。

主要な成果:

  • HARNNモデルは、データ拡張後、IoU（Intersection over Union）0.954という高い性能を達成しました。
  • モデルは、交差検証およびテストデータセットの両方で強力な予測精度を示しました。
  • LIMEは直感的な可視化を提供し、モデルの臨床的信頼性と理解を向上させました。

結論:

  • 経穴処方の予測のための階層的かつ解釈可能な機械学習モデルが正常に開発されました。
  • HARNNとLIMEの統合は、AMTの知能化のための新しい技術的アプローチを提供します。
  • 本研究は、個別化されたデータ駆動型鍼灸治療のための堅牢な方法論を提供します。