SynthesisBMC medical informatics and decision making2026
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).
Synthesis in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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