Integrating aqli (rationale) and naqli (revealed) knowledge in AI-driven clinical decision support systems to enhance healthcare delivery for guiding termination of pregnancy among Muslim patients: a systematic review (1)

Termination of pregnancy (TOP) is an important issue in perinatal health, yet culturally responsive clinical decision-making supports system (CDSS) surrounding TOP remains underexplored. The utilisation of artificial intelligence (AI) particularly in CDSS, is on the rise and can facilitate healthcare professionals (HCPs) in making clinical decisions for TOP. Clinical guidelines on TOP are relatively devoid of religious guidance, and in Muslim majority countries such as Malaysia, this deficiency imposes extra cognitive and psychological burden of reasonings upon HCPs, patients and families. There is also a paucity of evidence on integrated clinical and Islamic approach towards TOP CDSS for Muslim patients. This gap warrants a closer look at pregnancy termination among Muslim patients and CDSS impact on obstetric care, including barriers and facilitators of the AI-driven CDSS for TOP. Seven (7) databases search was conducted using related MeSH and individual terms. Forty-six articles for the áqli (rationale) and 59 items for the naqli (revealed) knowledge sections were included and synthesised. Key themes for the áqli knowledge for exploring AI-driven vs traditional CDSS are knowledge foundations, decisions, data inputs, and personalisation, while barriers uncover themes of ethics: bias and transparency; trust; and learning capacity. Facilitators’ themes are demographic data; hybrid AI-driven CDSS model; and multimodal data syntheses. The naqli component themes include knowledge from Quran, knowledge from hadith, and divergence of jurisprudence scholars. This review proposes an AI-driven time-sensitive CDSS for TOP framework among Muslim patients as a solution to address issues related to it. Gaps and future directions are also discussed.

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Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2026-02-26
DOI
https://doi.org/10.1186/s12911-026-03374-8
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating aqli (rationale) and naqli (revealed) knowledge in AI-driven clinical decision support systems to enhance healthcare delivery for guiding termination of pregnancy among Muslim patients: a systematic review (1)

Muhamad Rafiqi Hehsan, Nur Zaireena Zainal, Hayati Abdul Rahman, Nadeeya ‘Ayn Umaisara Mohd Nor et al.
BMC Medical Informatics and Decision Making
Artificial Intelligence in Healthcare and Education
article

Integrating aqli (rationale) and naqli (revealed) knowledge in AI-driven clinical decision support systems to enhance healthcare delivery for guiding termination of pregnancy among Muslim patients: a systematic review (1)

Muhamad Rafiqi Hehsan, Nur Zaireena Zainal, Hayati Abdul Rahman, Nadeeya ‘Ayn Umaisara Mohd Nor, Zizi Mohd Mohd Yusof, Lutfil Hadi Kamaruzaman, Nur Abdul Abdul Rahman
article en

Abstract

Termination of pregnancy (TOP) is an important issue in perinatal health, yet culturally responsive clinical decision-making supports system (CDSS) surrounding TOP remains underexplored. The utilisation of artificial intelligence (AI) particularly in CDSS, is on the rise and can facilitate healthcare professionals (HCPs) in making clinical decisions for TOP. Clinical guidelines on TOP are relatively devoid of religious guidance, and in Muslim majority countries such as Malaysia, this deficiency imposes extra cognitive and psychological burden of reasonings upon HCPs, patients and families. There is also a paucity of evidence on integrated clinical and Islamic approach towards TOP CDSS for Muslim patients. This gap warrants a closer look at pregnancy termination among Muslim patients and CDSS impact on obstetric care, including barriers and facilitators of the AI-driven CDSS for TOP. Seven (7) databases search was conducted using related MeSH and individual terms. Forty-six articles for the áqli (rationale) and 59 items for the naqli (revealed) knowledge sections were included and synthesised. Key themes for the áqli knowledge for exploring AI-driven vs traditional CDSS are knowledge foundations, decisions, data inputs, and personalisation, while barriers uncover themes of ethics: bias and transparency; trust; and learning capacity. Facilitators’ themes are demographic data; hybrid AI-driven CDSS model; and multimodal data syntheses. The naqli component themes include knowledge from Quran, knowledge from hadith, and divergence of jurisprudence scholars. This review proposes an AI-driven time-sensitive CDSS for TOP framework among Muslim patients as a solution to address issues related to it. Gaps and future directions are also discussed.

BMC Medical Informatics and Decision Making
Universiti Sains Islam Malaysia (MY), Sultan Zainal Abidin University (MY)
Gender equality
Openalex Percentile: Top 45%
Artificial Intelligence in Healthcare and Education
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