A critically high potassium result arrives for a patient who looks completely well. Your first instinct isn't to treat, but to question the sample. Should we be just as sceptical of the data behind medical AI?

This episode of The Health AI Brief dives into the most fundamental rule of artificial intelligence: junk in, junk out. Dr. Stephen uses the classic example of a haemolysed blood sample to explain why an AI model is only as reliable as the data it’s trained on. Discover how flawed data can mislead even the most sophisticated algorithms and learn three essential takeaways for critically appraising AI tools and trusting your clinical judgement in this new era of medicine.

#ai in medicine #ArtificialIntelligence #MachineLearning #DataQuality #JunkInJunkOut #GIGO #HealthcareAI #ClinicalDecisionSupport #MedicalAI #AIBias #TrainingData #DigitalHealth #CriticalAppraisal #EvidenceBasedMedicine #HealthTech

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