In this episode of Mobile Development with Fexingo, Lucas and Luna explore how on-device AI is being used to predict heart attacks in real time. They dive into a specific case: a 2025 study where a smartphone app analyzed pulse-wave data from the camera and accelerometer to flag atrial fibrillation and early signs of myocardial infarction. Lucas explains the technical pipeline — from photoplethysmography signal capture to a lightweight convolutional neural network that runs entirely on-device — and Luna questions the accuracy trade-offs and regulatory hurdles. They also touch on how Apple's Heart Study and Google's Health Connect APIs paved the way for this kind of deployment. No hype, just the real engineering and clinical challenges of turning a phone into a cardiac monitor.

#OnDeviceAI #HeartAttackPrediction #MobileHealth #AIinMedicine #Photoplethysmography #ConvolutionalNeuralNetworks #AtrialFibrillation #MyocardialInfarction #AppleHeartStudy #GoogleHealthConnect #RealTimeAI #SmartphoneDiagnostics #MachineLearning #iOSDevelopment #AndroidDevelopment #HealthTech #FexingoBusiness #BusinessPodcast

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