In brief
At Taibah University, the MCAIT 2026 conference introduced AI breakthroughs, including a cardiac arrhythmia model with 98.32% accuracy, a depression‑detection study on Arabic texts, and assistive tech for the visually impaired. Keynote talks explored AI’s future in Arabic language understanding, safe AI development, and evaluation challenges. The event also featured workshops and research on agriculture, cybersecurity, and drones for search and rescue.
During the second day of the MCAIT 2026 conference on Nov. 5, 2026, researchers from Taibah University and the Universiti Kebangsaan Malaysia showcased new AI breakthroughs at the university’s campus.
The agenda began with four keynote speeches. Speakers discussed the future of AI in understanding the Arabic language, creating safe and fair AI models through international collaboration, tracing the history of AI and the differences between specialized and general systems, and the difficulties of evaluating language models in real‑world conditions, especially when they must grasp local dialects and social contexts.
A dedicated workshop focused on building natural‑language processing tools with Transformer models, giving participants hands‑on experience with the latest AI architecture.
Parallel research sessions ran in person and online, covering a wide range of practical applications. In healthcare, a new model classified cardiac arrhythmias with an accuracy of 98.32 %. A separate study built an intelligent framework that monitors daily activities and pinpoints indoor locations for older adults. Deep‑learning techniques were used to spot lung tissue abnormalities with 98.38 % accuracy and to detect malaria early, achieving 99.12 % accuracy.
Arabic language research presented a study that analyzed roughly 22,000 classified Arabic texts to find linguistic signals linked to depression, reaching 95.85 % accuracy.
Other projects explored assistive technologies for people with visual impairments, combining computer vision and language models to describe surroundings and enable social interaction.
Further work demonstrated AI solutions for search‑and‑rescue missions using drones, smart agriculture and water‑resource management, as well as digital network protection that detects malware and monitors cyber threats.
Researchers also showcased models that improve irrigation efficiency and overall agricultural production, illustrating how AI can address environmental and everyday challenges.
Overall, the conference underscored AI’s growing impact across health, language, accessibility, and security, with a clear focus on real‑world applications and inclusive development.
