Rare kidney operation performed at King Faisal Specialist Hospital
RIYADH: King Faisal Specialist Hospital and Research Centre in Riyadh recently performed a rare Endoscopic Sleeve Gastroplasty on a patient who had previously undergone a kidney transplant.
In a statement, KFSHRC said the operation was considered 'the first of its kind in the region.'
It required 'meticulous management of immunosuppressive medications and the prevention of any complications that could jeopardize the transplanted organ.
'This procedure marks a significant advancement in providing safe treatment solutions for transplant recipients, to improve their graft survival and quality of life.'
The ESG procedure differs from surgical sleeve gastrectomy in that it requires no abdominal incisions, which is important for transplant patients.
Instead, it uses an endoscope inserted through the mouth to suture the stomach internally, effectively reducing its volume and enabling the patient to lose weight and improve overall health.
The procedure was performed by a multidisciplinary team of experts led by Dr. Ehab Abufarhaneh, consultant in adult transplant gastroenterology and hepatology.
The team included gastroenterologists, various transplant surgeons, anesthesiologists, and nursing staff.
In the statement, the hospital said it was 'adopting innovative techniques tailored to the unique needs of transplant patients and developing treatment protocols that address post-transplant challenges.'
The facility 'reinforces its position as a regional referral hub for cases beyond the scope of conventional treatment pathways,' and as a leading healthcare provider in the region.
It was fulfilling its vision of being the optimal choice for patients supported by an integrated ecosystem of education, research, and clinical excellence that aligns with Saudi Vision 2030, the hospital stated.
The hospital has been ranked by Brand Financing 2025 as first in the Middle East and North Africa, and 15th globally on the list of the world's top 250 Academic Medical Centers for the third consecutive year.
Additionally, it was included in the World's Best Smart Hospitals list for 2025 by Newsweek magazine.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Arab News
6 hours ago
- Arab News
Palestinian child arrives in Saudi Arabia for treatment under King Salman's directives
RIYADH: Palestinian Mohammed Khaled Hijazi, 7, arrived in the Kingdom on Thursday with his parents to receive medical care and was immediately transferred to the King Khaled Eye Specialist Hospital and Research Center in Riyadh. The supervisor general at the Saudi aid agency KSrelief, Dr. Abdullah Al-Rabeeah, thanked King Salman and Crown Prince Mohammed bin Salman for the humanitarian initiative to treat the Palestinian boy in the Kingdom. Al-Rabeeah said that Hijazi lost his right eye while his left eye was severely damaged by an explosion while he was playing with friends near their house, which was completely destroyed, in the Jabalia camp, north of Gaza, last month. The supervisor general prayed for the boy's speedy recovery and for the Palestinian people to be relieved of their suffering. He clarified that this initiative is a continuation of the relief and humanitarian efforts provided by the Kingdom to the Palestinian people in times of crisis and adversity, particularly the most vulnerable categories, such as children, who innocently pay the price of conflicts. Al-Rabeeah also saidthat the initiative is part of the humanitarian approach adopted by the Kingdom toward needy peoples through KSrelief, which does not discriminate based on gender, race, or religion, and is fundamentally rooted in noble human principles of compassion and human solidarity. The Palestinian boy's parents expressed their appreciation and gratitude to the Kingdom for treating their son, affirming that this brotherly gesture is not unusual from the Kingdom's leadership, which has always been known for its honorable stance in support of the Palestinian people.
Arab News
20 hours ago
- Arab News
How emerging AI talent is shaping the future of smart healthcare in Saudi Arabia
RIYADH: As Saudi Arabia accelerates its investment in AI-powered healthcare, two young researchers from the Mohamed bin Zayed University of Artificial Intelligence are building the very tools that hospitals in the Kingdom will soon need — intelligent, interpretable, and scalable systems for diagnosis and prognosis. Although the university's 2025 cohort did not include Saudi nationals this year, the work of two standout graduates, Mohammed Firdaus Ridzuan and Tooba Tehreem Sheikh, directly aligns with Saudi Arabia's healthcare transformation plans under Vision 2030. Their research offers practical, forward-looking solutions for the Kingdom's next generation of smart hospitals. At a time when AI systems are being deployed across diagnostic units in Saudi hospitals, from the King Faisal Specialist Hospital to new initiatives backed by the Saudi Data and AI Authority, the focus is shifting from capability to clarity. Can the systems provide real-time support? Can they explain their reasoning? Can doctors intervene? These are the questions both Ridzuan and Sheikh have set out to answer. Ridzuan, a PhD graduate in machine learning, developed Human-in-the-Loop for Prognosis, or HuLP for short — a cancer survival prediction system that places doctors back at the center of AI-powered decision-making. 'While AI has made significant strides in diagnosing diseases, predicting individual survival outcomes, especially in cancer, is still a challenging task,' Ridzuan told Arab News. 'Our model addresses this by enabling real-time clinician intervention.' Unlike traditional models that operate in isolation, HuLP is built for collaboration. Medical professionals can adjust and refine its predictions using their clinical expertise. These adjustments are not just temporary; they influence how the model evolves. 'Doctors and medical professionals can actively engage with the system,' Ridzuan said. 'Their insights don't just influence the result — they actually help the model learn.' This approach to human-AI partnership ensures that predictions remain explainable, context-aware, and grounded in patient-specific realities, a key need for Saudi hospitals integrating AI at scale. 'By allowing clinicians to dynamically adjust predictions, we create a more adaptive and responsive system that can handle local challenges,' Ridzuan added. The Kingdom's healthcare institutions are undergoing a digital transformation driven by national entities like SDAIA, the Ministry of Health, and the Center for Artificial Intelligence in Medicine and Innovation. These entities are focused not only on adopting new AI tools but also on ensuring that these systems can integrate into clinical workflows. This is where Ridzuan sees HuLP making an impact. 'Smart hospitals are already integrating AI diagnostic tools for medical imaging and patient data analysis,' he said. 'Our model can take this to the next level by empowering clinicians to interact with and guide the system's predictions.' In settings where trust and transparency are vital, Ridzuan's collaborative model could help hospitals overcome one of AI's most persistent problems: the black box effect. This refers to the opaque nature of certain systems, particularly in the field of AI, where the internal workings and decision-making processes are hidden or unknown. The emphasis on local relevance also comes through in HuLP's design. Ridzuan says real-time data from regional healthcare systems is essential for training accurate, context-sensitive models. 'Local data provides insights into the unique health conditions and medical practices within the Gulf region,' he said. 'Integrating this data ensures that the AI is attuned to the specific needs and health profiles of patients in the region.' The system is built to learn continuously. As clinicians correct or refine its predictions, the model updates itself, improving with each interaction. This feedback loop is crucial for real-world deployments, especially in the Gulf, where data quality can be inconsistent. While Ridzuan is focused on outcomes, Sheikh, an MSc graduate in computer vision, is transforming the way hospitals detect disease in the first place. Her project, Med-YOLOWorld, is a next-generation imaging system that can read nine types of medical scans in real time. Unlike traditional radiology AI tools, which are often limited to specific tasks, Med-YOLOWorld operates with open-vocabulary detection. That means it can identify anomalies and organ structures that it has not been explicitly trained on — a key feature for scalability. 'Most models are confined to a single modality like CT or X-ray,' Sheikh told Arab News. 'Med-YOLOWorld supports nine diverse imaging types, including ultrasound, dermoscopy, microscopy, and histopathology.' With support for up to 70 frames per second, the system is designed for clinical deployment in high-demand environments. Sheikh sees clear potential for its use in Saudi Arabia, where institutions like the King Faisal Specialist Hospital and Research Centre are already implementing multi-modal AI imaging tools. 'It can seamlessly integrate with existing imaging systems to enable open-vocabulary detection,' she said. 'Identifying a wide range of medical findings — even those outside its original training set — is essential for fast-paced clinical environments.' But building a universal imaging tool came with its own technical hurdles. 'The biggest challenge was managing the diverse preprocessing requirements across imaging modalities,' Sheikh said. 'CT and MRI scans need intensity normalization, while ultrasound, dermoscopy, and microscopy have completely different visual characteristics.' Data imbalance was another issue. While MRI and CT scans are widely available, data for more niche imaging types is scarce. Sheikh tackled this by designing custom augmentation techniques to ensure the model performs consistently across all modalities. She is now working on combining Med-YOLOWorld with vision-language models, systems that explain what they see in natural language. 'MiniGPT-Med does a great job at explaining radiology images,' she said. 'But pairing it with a system like Med-YOLOWorld adds a crucial dimension — open-world localization. Not just describing the issue but pointing to it.' This fusion could create a powerful end-to-end diagnostic pipeline: detect, explain, and localize. For Saudi hospitals embracing AI-driven imaging, the impact could be transformative. For Sheikh, the global implications of her work are just as important as the technical achievements. 'Med-YOLOWorld reduces the need for large, annotated datasets,' she said. 'In fast-scaling healthcare systems, that's a game-changer.' By enabling the detection of unseen categories, the system can remain relevant even as new diseases or anomalies emerge. And when combined with language models, it can assist in medical training, annotations, and decision support, all while reducing dependence on expert-labeled data. This approach could accelerate AI adoption in emerging regions, including across the Gulf and the wider Middle East and North Africa, where access to large datasets and AI-specialized radiologists remains limited. While MBZUAI is based in the UAE, its alumni are playing a growing role in shaping AI initiatives that extend across the Gulf. Both Ridzuan and Sheikh have demonstrated how innovation, when aligned with clinical realities and regional goals, can scale far beyond the lab. As Saudi Arabia continues to invest in smart hospitals, real-time imaging, and personalized care, tools like HuLP and Med-YOLOWorld represent the next wave of AI in healthcare: explainable, collaborative, and regionally adaptable. And with growing partnerships between research institutions, healthcare providers, and government entities, these systems may not be far from deployment in the Kingdom, paving the way for a more intelligent, human-centered approach to medical care.
Arab News
21 hours ago
- Arab News
KSrelief clinics help refugees in Jordan
AMMAN: The clinics of the King Salman Humanitarian Aid and Relief Center provided healthcare services to 2,789 patients in Zaatari camp for Syrian refugees in Jordan during the first week of May. The general medicine clinics received 778 patients, while the internal medicine clinic treated 128 patients with diabetes, high blood pressure, and asthma. The pediatric clinics received 226 children, 131 patients visited dental clinics, and 312 women were treated by the two women's health clinics. The ear, nose, and throat clinic received 66 patients suffering from sinusitis, pharyngitis, tonsillitis, and middle ear infections. The ophthalmology clinic saw 37 patients. The cardiology clinic received 15 patients, the diagnostic radiology clinic received 37 patients, and the rehabilitation medicine clinic also treated 37 patients. A total of 3,245 laboratory tests were conducted for 284 patients, and 217 imaging procedures, including X-ray and ultrasound examinations, were performed for 184 patients.
