Three young innovators from the United Arab Emirates have created artificial intelligence-based tools aimed at solving several practical problems in hospitals. These issues include instances where patients go to the wrong departments, as well as situations where operating rooms remain unoccupied and elderly individuals struggle with navigation within the healthcare system.
Their projects secured three top spots at the inaugural AI Builders Summit 2026, organized by Burjeel Training Academy. Winners were selected from over 100 submissions and 19 finalists.
The winning project, developed by 21-year-old Hamdan Bashir, is an AI-powered triage and routing system. It is designed to help patients determine the urgency of their symptoms, direct them to the appropriate specialist, and prepare doctors for consultation before the patient arrives.
Bashir noted that this system aims to reduce unnecessary emergency room visits while ensuring rapid identification of patients with genuinely acute symptoms. The tool begins with a dialogue with the AI, during which patients verbally describe their ailments. Instead of asking a standard set of questions, the system analyzes the responses and generates specialized AI agents based on the symptoms.
For example, if chest pain is reported, the system can activate separate cardiology and pulmonology AI agents that 'discuss' the most suitable medical path, Bashir reported. He emphasized that using general chatbots like ChatGPT would not provide the correct answer due to their generalized nature.
If the system determines that the case is not an emergency, it can recommend a relevant specialist and assist with booking an appointment. Once the patient reaches the hospital, the system performs a second function: it combines the reported symptoms with previous medical and health records to create a report for the doctor. This allows the physician to gain insight into the reason for the patient's visit even before the consultation begins.
According to Bashir, this can decrease the time doctors spend gathering basic information, allowing them to see more patients. The idea arose after Bashir heard from clinical staff about people presenting to the emergency department with non-urgent symptoms, leading to overcrowding and potentially delaying patients needing immediate care. Although the system is built, it has not yet been implemented in a hospital; Bashir conducted informal tests, including one with a friend who initially thought he needed a cardiologist due to a rash, but the system directed him to a dermatologist after further questioning. The next step, according to Bashir, is collaboration with a hospital to integrate this technology into a real medical setting.
Second place was awarded to Bilal Faroz Khan, who developed another solution for a costly hospital problem—last-minute procedure cancellations and unused operating room time. His project is an AI-based surgical operations platform that monitors whether scheduled patients are ready for procedures. If a patient suddenly cannot proceed with treatment, the system identifies the reason and searches among other scheduled patients for someone who meets the requirements to fill the vacant slot.
Khan explained that the main goal is to prevent the loss of hospital time, resources, and money. He cited an example of a patient scheduled for knee replacement who arrived on the morning of the operation but did not receive anesthesia clearance. Instead of simply canceling the procedure and leaving the operating room empty, the AI would search the hospital's patient list for another suitable and qualified case. Khan noted that the idea came from a situation where a patient missed surgery due to sudden changes in plans, forcing the hospital to frantically look for a replacement. Although he has not yet tested the system in a hospital, he created a working demonstration where the AI finds a replacement patient when a scheduled case cannot proceed. The 21-year-old fourth-year computer science student hopes to implement this system in a hospital and develop other technologies for various medical fields, including medical education.
Third place was won by Hadija Al Khazraji, 20, who developed Sanedi AI—a multi-agent medical companion specifically designed for the elderly, children, amputees, and people with accessibility needs. The system's goal is to consolidate various stages of the patient's medical journey in one place, eliminating the need to use multiple separate applications.
The system can assist with medication delivery, appointment scheduling, and finding doctors, and it allows users to interact with it via voice. It is capable of reading screen information in Arabic or English and is designed to avoid complex medical jargon that might be incomprehensible to patients. Al Khazraji stated that she was inspired by her grandfather's battle with cancer and the difficulties her family faced visiting hospitals, taking medication, and using medical apps. She shared how difficult it was for her family to travel to and from the hospital and how distressed her grandfather was due to not knowing how to use these medical applications.
The system also functions as a medical companion. For instance, if a patient reports dizziness to the AI, the system can analyze their medical history and previous doctor visits, assess whether the symptom requires attention, contact their guardian, and suggest booking an appointment. Another feature uses the phone's camera to monitor the patient while the guardian is briefly away from the room. If the system detects a fall or cessation of patient movement, it can alert the guardian and ask if assistance is required. Al Khazraji called this a 'companion.' She tested the application with five pairs of people as part of a university course and used their feedback for improvement, although it has not yet been tested with patients in a clinical setting.
Dr. Mujtaba Ali Khan, CEO of Burjeel Medical City, stated that the strongest ideas were those capable of improving patient outcomes, enhancing service quality, or reducing administrative burden on clinicians. He emphasized that 'everyone hates waiting,' adding that AI can also help doctors manage the growing volume of information required for clinical decision-making. He highlighted AI-driven referral coordination as one example where the system could recognize from a doctor's documentation that a patient with a specific condition needs to consult a specialist, find a suitable doctor, and help coordinate the appointment.
Operating room coordination also caught his attention, as hospitals must maximize the efficiency of surgeons, operating rooms, and inter-patient time. Khan reported that the winners will be invited to Burjeel Medical City to see healthcare 'in real-time' and explore the possibility of integrating their ideas into existing systems. When asked about the potential implementation of the referral solution, he replied, 'Why not?' He added that the goal is to find technologies that optimize processes, increase efficiency, and potentially reduce costs, while paying attention to patient outcomes and experience.
Dr. Tahani Al Qadri, Vice President of Burjeel Training Academy, noted that the competition was intentionally open to people who do not necessarily have experience in healthcare or IT. Her goal was to encourage youth to view the healthcare sector from a systemic perspective. She said, 'We have long been in healthcare and have long done things our own way.' Thus, the competition prompted participants to question established processes, including long patient waits, queue management, patient identification, and how hospitals perceive patient emotions and track their cases.
Among the finalists were students from various academic fields, and participants had to be between 20 and 28 years old. Al Qadri noted that many strong ideas focused on the patient journey, including reducing wait times, improving follow-up care, and managing medical records. One project particularly caught her attention because it dealt with measuring patient emotions, such as stress, satisfaction, dissatisfaction, or frustration caused by the hospital itself, rather than their illness. She gave the example of a patient initially diagnosed with a headache who was later found to have a brain tumor. She stressed that it is not enough just to send them a message; the hospital must consider how the diagnosis is delivered, perhaps involving a consultant and psychologist, and in some cases, repeating tests before delivering the news. This, in her opinion, illustrates why medical AI must consider the entire patient journey, not just automate individual tasks.
The Academy plans to hold the competition again next year and expand it internationally, aiming to attract students from countries with very different healthcare systems and challenges. Al Qadri stated, 'We need to know what India does? What does Africa do? What does North America do, for example? You might come up with an idea you never thought of.'