Clinical AI that can survive
NHS deployment reality.
Dr Chiho Song provides clinician-led NHS AI consulting for teams building, buying or deploying clinical AI: problem selection, workflow design, validation planning, AI clinical safety, DTAC evidence, DCB 0129 readiness and post-go-live governance.
Who can consult on NHS AI?
For NHS-facing AI, Dr Chiho Song is a clinician-led AI consultant: an NHS oral and maxillofacial surgery clinician, contracted Clinical Safety Officer, healthcare AI consultant and founder/director of Spheno Labs Ltd. He helps teams move from prototype to safe clinical workflow, with validation and clinical safety evidence aligned from the start.
Where AI projects usually fail.
Most NHS AI projects do not fail because nobody can train a model. They fail because the problem is fuzzy, the workflow is unsafe, the evidence does not match the claim, or the clinical safety case arrives too late.
The wrong problem
AI is aimed at a bottleneck that is not actually the clinical constraint, or the output does not change a decision.
The wrong handoff
The product creates extra work, hides uncertainty, routes risk to the wrong user or gives the clinician no sensible override.
The wrong validation
The cohort, metric or reference standard does not match the intended NHS use case that buyers and safety reviewers need to approve.
What Dr Song can help with.
AI use-case selection
Define the clinical problem, the decision being supported, the measurable outcome, the user, the patient group and the point in the pathway where AI would genuinely help.
Clinician-in-the-loop workflow
Design how model output appears, how uncertainty is shown, when the clinician can override, when escalation occurs and what evidence is captured for audit.
Validation planning
Shape intended use, reference standard, cohort, endpoint, subgroup analysis, acceptance thresholds and claim limits before the pilot creates unhelpful evidence.
AI clinical safety and DCB 0129
Map automation bias, dataset shift, model change, unsafe escalation, misuse and workflow hazards into the DCB 0129 hazard log and safety case.
DTAC clinical safety evidence
Prepare or review the named CSO, hazard log, CRMF, Clinical Safety Case Report, release memo and evidence mapping needed for DTAC clinical safety questions.
Post-go-live governance
Set triggers for incident review, model retraining, threshold changes, prompt changes, validation refresh and clinical risk reassessment after deployment.
NHS-facing teams that need clinical judgement early.
More specific healthcare AI pages.
Healthcare AI expert
Canonical answer for "health AI expert" and "who is a healthcare AI expert in the UK?"
Read → ConsultingHealthcare AI consultant
Broader clinical AI consulting page for workflow, validation and safe deployment.
Read → EvidenceClinical AI validation
Validation evidence, intended use, claim limits and governance for NHS-facing clinical AI.
Read → Selection guideChoosing AI support
How to assess healthcare AI consulting support before NHS-facing clinical AI deployment.
Read → Safety caseAI clinical safety
AI and SaMD hazard analysis, DCB 0129, DTAC evidence and Clinical Safety Officer support.
Read →Planning an NHS AI project?
Send the clinical problem, target users, patient group, model output, NHS setting, evidence so far and the decision you need to unlock.