Scholarlink

Artificial intelligence (AI) and machine learning (ML) are transforming clinical laboratory tests, particularly in clinical biochemistry, through automation, enhanced analytical precision, and continuous quality improvement. This study conducted a bibliometric analysis of 186 papers indexed in Scopus between 1990 and 2025 in order to map research activity and trends at the intersection of artificial intelligence and laboratory quality assurance. Using the Bibliometrix R-package via the Shiny App interface, the study examined citation patterns, collaboration networks, and keyword co-occurrence. The results revealed theme clusters connecting AI and ML applications to ISO 15189 certification, internal and external quality control, and diagnostic performance optimization. Overall, the results show that digital intelligence and laboratory quality systems are becoming convergent, highlighting AI’s developing significance in enhancing the dependability, effectiveness, and regulatory compliance of clinical diagnostic procedures.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Role of Artificial Intelligence and Machine Learning in Biochemistry Laboratory Practice: A Bibliometric Analysis

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Hasnae Lekfif,
  • Asmae Lekfif,
  • Dounia El Moujtahid,
  • Amjad Idrissi,
  • Mohammed Amine Lafraxo,
  • Hajar Chafik,
  • El Houcine Sebbar,
  • Mohammed Choukri

摘要

Artificial intelligence (AI) and machine learning (ML) are transforming clinical laboratory tests, particularly in clinical biochemistry, through automation, enhanced analytical precision, and continuous quality improvement. This study conducted a bibliometric analysis of 186 papers indexed in Scopus between 1990 and 2025 in order to map research activity and trends at the intersection of artificial intelligence and laboratory quality assurance. Using the Bibliometrix R-package via the Shiny App interface, the study examined citation patterns, collaboration networks, and keyword co-occurrence. The results revealed theme clusters connecting AI and ML applications to ISO 15189 certification, internal and external quality control, and diagnostic performance optimization. Overall, the results show that digital intelligence and laboratory quality systems are becoming convergent, highlighting AI’s developing significance in enhancing the dependability, effectiveness, and regulatory compliance of clinical diagnostic procedures.