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相关概念视频

Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
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Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

Cardiovascular Drugs: Classification based on Therapeutic Indications

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Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
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Classification of Illness01:17

Classification of Illness

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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Combined Effects of Drugs: Synergism01:27

Combined Effects of Drugs: Synergism

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Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
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Peptide Identification Using Tandem Mass Spectrometry01:33

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
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MALDI-TOF Mass Spectrometry01:19

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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.
Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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相关实验视频

Updated: Jun 11, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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MeSH2Matrix:结合MeSH关键字和机器学习,基于PubMed进行生物医学关系分类.

Houcemeddine Turki1, Bonaventure F P Dossou2,3, Chris Chinenye Emezue2,4

  • 1Data Engineering and Semantics Research Unit, Faculty of Sciences of Sfax, University of Sfax, Sfax, Tunisia. turkiabdelwaheb@hotmail.fr.

Journal of biomedical semantics
|October 1, 2024
PubMed
概括

这项研究引入了MeSH2Matrix,一个新的数据集和生物医学关系分类方法. 它通过使用医学科目标题 (MeSH) 资格符来增强机器学习模型,提高分析科学文献的准确性和可靠性.

关键词:
生物医学关系分类的分类.特性分析 特性分析集成梯度的集成梯度是指集成的梯度.机器学习 机器学习一个MeSH关键字的关键词.在MeSH的资格赛中,在PubMed的记录中,PubMed的记录记录.

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科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 医疗信息学 医疗信息学

背景情况:

  • 先进的机器学习改进了从学术文本中对生物医学关系的分类.
  • 依赖原始文本限制了当前方法的概括性,精度和可靠性.
  • 文献元数据为提高这一任务的性能提供了潜力.

研究的目的:

  • 引入一种用于生物医学关系分类的方法,使用同时出现的医学主题标题 (MeSH) 的合格符.
  • 介绍MeSH2Matrix,这是一个来自PubMed的46,469个生物医学关系的新型数据集.
  • 评估MeSH资格器在改进分类模型方面的有效性.

主要方法:

  • 开发了MeSH2Matrix数据集,映射了MeSH合格符协会和维基数据关系类型.
  • 从PubMed出版物中策划了46,469个生物医学关系.
  • 在MeSH2Matrix数据集上训练和评估了三种机器学习模型 (SVM,D-Model,C-Net).

主要成果:

  • 最好的模型在195个关系类中达到70.78%的准确率,在5个超级类中达到83.09%.
  • 特征分析检查了MeSH资格符号和分类生物医学关系之间的关系.
  • 混矩阵提供了对模型性能的详细见解.

结论:

  • 使用MeSH合格器为增强生物医学关系分类提供了一个有希望的途径.
  • MeSH2Matrix数据集和方法可以导致更准确的生物医学本体学分类.
  • 公共可访问的数据集和代码有助于可复制性和进一步研究.