Dr Talal Al-Mayhani

Dr Talal Al-Mayhani is a consultant neurologist with extensive clinical experience in the diagnosis and management of a wide range of neurological disorders, including complex and diagnostically challenging presentations.

He has worked in the NHS, providing consultant-level care across different sites: 

* The UCLH Hyper-Acute Stroke Unit (HASU) and TIA (mini stroke) clinics at Queen Square, London

* The Complex Neurovascular Clinic at Queen Square, run in conjunction with colleagues from Neurosurgery and Interventional Neuro-Radiology, London

* The neurology ward at Royal Free Hospital, London

* Leading the Epilepsy Service at Bedfordshire Hospitals NHS Foundation Trust, Luton

* General neurology outpatient clinics at Luton & Dunstable University Hospital, Luton

He trained at several of the UK’s leading medical and academic neuroscience centres, including the National Hospital for Neurology and Neurosurgery (Queen Square), the Royal Free Hospital, University College London and the University of Cambridge, and completed his Specialist Training in Neurology in London. 

In addition to his clinical commitments, Dr Al-Mayhani has a longstanding interest in medical education and runs regular small and large group teaching sessions to the undergraduate medical students and postgraduate neurology trainees.

He is fluent in Arabic.

Research interests

Dr Al-Mayhani has a strong academic background, having completed a PhD at the University of Cambridge’ Department of Clinical Neuroscience. His doctoral research in brain repair and neuro-oncology explored the neural stem cells and brain cancer, with particular focus on glioblastoma, one of the most common types of brain malignancies.

Following his doctoral research, his academic interests developed towards clinical neurology, particularly stroke, stroke mimics and epilepsy. His research has included the investigation of stroke pathways, the use of telemedicine and video assessment in acute stroke, the SMART Project for stroke mimics and the application of artificial intelligence to clinical decision-making in stroke and selection of anti-seizure medication for epilepsy.