AI and Arabic Medical Language Processing: Towards More Accurate Clinical Documentation
By Dr Youssef Ghaly and Dr Mostafa Helmy · Published November 2025
The full paper is written in Arabic — this page summarises it in English.
Abstract
This Arabic-language whitepaper (INTL-2026-008, November 2025) analyzes why Arabic is among the most challenging languages for clinical natural language processing: a root-and-pattern morphology, right-to-left script, dialects that differ fundamentally from Modern Standard Arabic, constant Arabic-English code-switching, and Arabic, English, and Latin medical terms mixed within a single sentence. It concludes with ClinixSummary's reported results in Arabic medical language processing: 93% Arabic medical-term recognition accuracy, 94% code-switching handling accuracy, a 91% note acceptance rate in bilingual environments, and dialect coverage spanning Gulf, Egyptian, Levantine, and Maghrebi Arabic.
What the paper covers
Morphological complexity of Arabic
Arabic morphology is built on a root-and-pattern system: from the triliteral root k-t-b derive words such as katib, maktub, kitaba, maktab, and kitab. Because a single word can take dozens of different forms, recognizing medical terminology is more complex than in European languages.
Arabic dialects in the clinical setting
There is a fundamental gap between Modern Standard Arabic and the local dialects physicians use with patients daily, with Gulf, Egyptian, Levantine, and Maghrebi dialects each using different words for symptoms and diseases. The paper illustrates each dialect with an example symptom phrase mapped to its standard-Arabic meaning (e.g., Gulf "endi sudaa w harara" = "I have a headache and fever").
Code-switching in clinical practice
Arabic-English code-switching is a defining feature of clinical practice in the Arab world: a physician may say, in one sentence, that the patient has "chest pain" and "shortness of breath," the "ECG" is normal, but the "troponin" is slightly elevated. This mixed pattern is completely natural in Arabic clinical environments yet poses a major challenge for NLP systems.
Terminological duality in Arabic medicine
Arabic carries a rich medical heritage from the Golden Age of Islamic civilization — Ibn Sina, Al-Razi, and Ibn al-Nafis established Arabic medical terms still in use today. Yet many modern medical terms are used in English in daily practice, creating a terminological duality that clinical documentation systems must handle.
Reported performance results
The paper states that ClinixSummary achieved advanced results in Arabic medical language processing: 93% accuracy in recognizing Arabic medical terminology, 94% accuracy in handling code-switching, and a 91% note acceptance rate in bilingual environments. Dialect coverage spans Gulf, Egyptian, Levantine, and Maghrebi Arabic.
Figures and statements reflect the paper as published in November 2025.