Clinical Neurology
From acute stroke and seizure to the slow puzzles of headache, demyelination, and movement disorders. The answer is sometimes on the MRI — more often it’s hiding in the history.
Contents: fig. 00, in rotationAffect: appropriateGrooming: immaculateS1, S2 present. No murmursI’m Abdulrahman Alhayssoni, a neurology resident at King Saud University Medical City. By day I examine brains. After hours I study the machines learning to read them — and help write the rules that keep them honest.
Neurological exams, ward rounds, and the small detective work of finding out what a brain is trying to say. That’s the day job. The after-hours question: what happens when the next stethoscope is a model?
Governance is the unsexy scaffolding — policy, audit trails, consent — that decides whether a tool helps a patient or harms them. I work on that, and on the harder part: bringing models into clinics without spending trust it took medicine a century to earn.
Continue neurology residency. Research the safe use of large models in clinical workflows — diagnostics, triage, documentation. Audit the quiet ethics underneath. Reassess daily.
312+
Reflexes elicited
Patellar, Achilles, biceps. The hammer never sleeps.
9,847 lines
Vibe-coded
Mostly working. Some commented. A few prayed over.
1,240 hrs
In the on-call room
Fluorescent light, vending-machine coffee, character development.
47
Whiteboard markers killed
Mostly during ward rounds. RIP, blue.
From acute stroke and seizure to the slow puzzles of headache, demyelination, and movement disorders. The answer is sometimes on the MRI — more often it’s hiding in the history.
Bringing models into the clinical loop without breaking it — radiology assist, decision support, ambient documentation, and the workflows around them.
LLMsDecision SupportImagingWorkflows
Policy, audit, validation, and consent. How a hospital decides what a model is allowed to do — and what to do when it’s wrong.
RiskAuditConsentBias
Patient-facing tools, remote monitoring, and the long quiet design problem of meeting people where they actually are.
TelehealthRPMUXPublic Health
Talks, panels, and short essays for clinicians learning to think about AI — and for technologists learning to think about medicine.
TalksEssaysMentoring
Saïd Business School, University of Oxford — focused on IT governance, AI policy, and regulation.
ID 9HJEWCCB94FC
Oxford · verified
IBM — applied machine learning fundamentals in Python, from preprocessing through evaluation.
ID GY310JOYXD1U
IBM · verified
IBM — software engineering practices, version control, and collaborative development workflows.
ID WPE8NH1N3TL6
IBM · verified
McKinsey & Company — leadership, problem-solving, and communication frameworks for early-career professionals.
ID — on file
McKinsey · verified
King Saud University Medical City · Riyadh
Inpatient service, outpatient clinics, and the on-call phone. Between admissions: working out how AI tools earn a place in everyday hospital workflows — safely, and on the record.
NarraLabs · Part-time
Part-time interpreter between two dialects: what clinicians actually need, and what AI teams actually build. Steered healthcare-AI engagements through governance, validation, and adoption.
King Saud University · Riyadh
Rotated through internal medicine, surgery, ED, pediatrics, and ob-gyn. Gravitated toward neurology — the discipline that rewards listening more than ordering.
King Saud University · Riyadh
Ran the college’s student club — timelines, budgets, a full calendar of academic and community events. Learned to ship things with a team that keeps hospital hours.
King Saud University · Riyadh
Led student initiatives through a year that asked everyone to work differently. Programming, budgeting, mentorship — much of it over webcam.
King Saud University · Riyadh
The link between the college and the batch — schedules, announcements, and the small, constant logistics of keeping a medical cohort pointed the same way.
King Saud University · Riyadh
Six years of medicine, biostatistics, and the slow craft of clinical reasoning. Started a habit that hasn’t stopped: reading something clinical and something computational every week.
Electronically signed
A. Alhayssoni
Neurology × AI · no cosign required