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Infertility in Females01:28

Infertility in Females

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Female infertility is defined as the inability to conceive after a year of regular, unprotected intercourse and affects about 10–15% of couples worldwide. The primary cause of female infertility is ovulatory disorders, which hinder the release of eggs. These disorders can be classified as hypothalamic amenorrhea, polycystic ovarian syndrome (PCOS), premature ovarian failure, and hyperprolactinemic anovulation disorders.
Endometriosis, a condition characterized by abnormal growth of...
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Infertility in Males01:23

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Male infertility affects millions of couples worldwide, arising from various factors that impact different stages of the reproductive process. An endocrine imbalance resulting from conditions like hypogonadism, Klinefelter syndrome, or pituitary disorders can disrupt hormone levels and reduce sperm production. Testicular defects, such as tumors, cryptorchidism, atrophic testes, abnormal sperm morphology, and low sperm count or motility, may arise due to genetic factors, structural...
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In vitro fertilization (IVF) is a form of assisted reproductive technology where an egg is fertilized with sperm in a controlled laboratory environment before transferring the resulting embryo into the uterus. This process is designed to help individuals and couples experiencing difficulties conceiving.
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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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不妊症における意思決定支援システムの概念モデルの提示：開発研究

Hasan Sajjadi1, Hamid Choobineh2,3, Reza Safdari1

  • 1Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

International journal of reproductive biomedicine
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PubMed
まとめ

本研究では、不妊症意思決定支援システムの概念モデルを開発した。専門家の意見とデータ分析に基づいたこのモデルは、不妊症患者の診断と治療の精度を向上させることを目的としている。

キーワード:
人工知能不妊症インテリジェントシステムエキスパートシステム

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科学分野:

  • 生殖医学
  • 医療情報学
  • ヘルスシステム工学

背景:

  • 不妊症は、1年以上妊娠を試みている個人に影響を与え、意図しない不妊につながります。
  • 臨床意思決定支援システム（CDSS）は、不妊症の診断を改善し、コストを削減し、治療の精度を高める可能性を提供します。

研究 の 目的:

  • 不妊症ケアに特化した意思決定支援システムの開発のための概念モデルを提示すること。
  • 文献、既存システム、専門家の意見からのデータを統合して、包括的なモデルを作成すること。

主な方法:

  • 文献レビュー（PubMed、Scopus、Web of Science）、既存システムの特定（Google、Yahoo、Bing、AIツール）、専門家調査（32名の専門家）を含む3段階の開発研究。
  • 研究者設計の質問票を用いて専門家の意見を収集し、信頼性（クロンバックのα=0.78）と妥当性（CVR=0.60）を確立しました。
  • データ分析には、体系的な文献検索、類似システムの競合分析、専門家のコンセンサスの統計分析が含まれました。

主要な成果:

  • 文献およびシステム検索により、それぞれ10件および13件の関連システムが特定されました。
  • 専門家コンセンサスは、モニタリング、精液分析、流産データを含む、不妊症管理のための主要なデータ要件について高い合意（82.5％～94％）に達しました。
  • 主な機能、患者情報管理、妊娠予測、二次的機能を含む概念モデルは、85％の全体的な専門家合意を達成しました。

結論:

  • 不妊症のための意思決定支援システムは、臨床ケアと患者の転帰を進歩させる可能性を秘めています。
  • 実装における主な課題には、検証方法の標準化と、システム設計における民族的多様性の考慮を確実にすることが含まれます。