Artificial intelligence tools designed to cut hospital waiting times, fill operating-room slots after last-minute cancellations and improve patient referrals have been developed by students in the UAE, targeting everyday pressures that can delay treatment and leave valuable healthcare resources unused.
The new systems could help hospitals respond more quickly when surgery slots unexpectedly become available, guide patients towards the appropriate medical service and prevent important follow-up recommendations from being missed.
The projects were showcased at the AI Builders Summit 2026, where young innovators developed working prototypes aimed at challenges affecting patients and healthcare teams. Rather than concentrating solely on diagnosis, many of the projects looked at the operational problems that happen before, during and after treatment.
Among the ideas were AI-powered triage, smarter management of cancelled surgery slots, improved medical record preparation and technology to keep referrals and follow-up care on track.
AI could guide patients to the right care
One of the standout projects was PRISM, developed by Hamdan Basheer of 42 Abu Dhabi.
The AI-powered triage and referral platform allows patients to describe their symptoms through a conversational interface. It then organises the information to help assess how urgently medical attention may be required and what type of care could be appropriate.
For healthcare professionals, PRISM is designed to bring patient-reported symptoms together with available clinical information and highlight potential warning signs.
The project received the Gold Prize at the summit.
Its focus reflects a familiar challenge for patients: deciding where to seek help. Someone experiencing symptoms may be unsure whether they require emergency treatment, a specialist consultation or another healthcare service. Entering the wrong part of the system can mean additional appointments and longer waits while also adding pressure to already busy services.
AI-assisted triage could help make that first step more efficient, although systems influencing clinical decisions would require extensive testing and professional oversight before being introduced into routine patient care.
Tackling unused operating room time
Students also explored how technology could address the disruption caused by last-minute surgery cancellations.
Operating rooms require considerable coordination. Surgeons, nurses, anaesthesia teams, equipment and other resources may all be scheduled around a single procedure.
When an operation is cancelled unexpectedly, hospitals can be left with valuable theatre time that is difficult to reallocate at short notice, even when other patients are waiting for procedures.
AI-based systems could help identify suitable patients who are medically prepared and potentially available to take the vacant slot, allowing hospitals to respond faster when their schedules change.
The technology would not prevent cancellations, but better matching and scheduling could reduce wasted capacity while potentially allowing another patient to receive treatment sooner.
AI projects go beyond diagnosis
Other students focused on different stages of the patient journey.
CaseReady AI, developed by Al Ain University student Bilal Feroz Khan, received the Silver Prize. The platform is designed to organise patient information and identify missing details, potentially making case preparation more efficient for healthcare teams.
Abu Dhabi University student Khadeja Al Khazraji received the Bronze Prize for Sanadi AI, which focuses on communication and coordination between patients, doctors and caregivers.
Other concepts tackled hospital navigation, referrals and follow-up care.
CarePath E-Ink was designed to help patients navigate hospitals through directions, queue information and multilingual notifications.
Another project, THREAD, addressed what happens after a radiology report recommends further action. The system aims to turn those recommendations into trackable steps, reducing the risk of an important follow-up being overlooked as a patient moves between different stages of care.
Together, the projects show how AI could play a role in healthcare without necessarily making a diagnosis. Improving scheduling, organising information and ensuring patients complete the next step in their treatment could also have a meaningful impact.
From student prototypes to real hospitals
The bigger challenge will be turning promising prototypes into technology that can operate safely in real healthcare environments.
Medical AI must meet demanding standards for accuracy, reliability, patient privacy, cybersecurity and clinical governance. A system that works during a demonstration still needs to prove that it can perform consistently across different patients and real-world situations.
Participants at the summit were prohibited from using real patient information while developing their projects. Instead, they worked with synthetic, mock or publicly de-identified data.
Human oversight would also remain essential, particularly for technology involved in triage, referrals or other decisions that could affect patient care.
For the students, the next stage is therefore not simply improving the technology, but demonstrating that their ideas can be validated and safely integrated into existing healthcare systems.
Hospital waiting times, missed follow-ups and unused operating-room capacity are not theoretical problems.
By starting with those problems rather than the technology itself, UAE students are showing another side of the AI boom one focused less on what artificial intelligence can promise and more on whether it can solve problems that hospitals already face.