The Digital Health Podcast with Fexingo: Wearables, Diagnostics, and Health Software

Episode 116 digs into how artificial intelligence is turning smartwatch biometrics—heart rate variability, skin temperature, overnight pulse—into predictions for ovulation, cycle timing, and fertility windows. Lucas and Luna examine the study from the University of Oxford that tracked 1,500 participants using Oura Rings and Apple Watches, where the AI model predicted menstrual phases with 80 percent accuracy. They discuss why Big Tech is investing in female health, the privacy trade-offs of sharing cycle data with a third-party app, and the future of personalized reproductive health tracking. No fluff, just the numbers and the science.

#MenstrualHealth #Femtech #Wearables #AIinHealthcare #DigitalHealth #OuraRing #AppleWatch #FertilityTracking #CycleTracking #OvulationPrediction #HeartRateVariability #SkinTemperature #UniversityOfOxford #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #DataPrivacy #ReproductiveHealth

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Over 25 million Americans have asthma, and most still use a 'dumb' inhaler — plastic canister, no data. In this episode, Lucas and Luna look at how sensor-equipped smart inhalers are changing that. They focus on Propeller Health, the company that added a Bluetooth attachment to standard rescue inhalers and logged over 100 million medication events. Lucas explains how the data — time, location, frequency — feeds a machine-learning model that predicts asthma attacks before symptoms start, reducing emergency room visits by 60 percent in one real-world study. But he also gets into the adoption barriers: insurance coverage, patient privacy, and whether the device actually changes behavior or just measures it. Luna pushes back on the 'gadget trap' — does sticking a sensor on an inhaler really help, or is it a solution in search of a problem?

#PropellerHealth #SmartInhaler #AsthmaTech #DigitalHealth #RespiratoryCare #Wearables #ConnectedDevices #MachineLearning #PreventiveCare #HealthData #MedicationAdherence #Business #Technology #Innovation #Healthcare #FexingoBusiness #BusinessPodcast #HealthTech

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In this episode, Lucas and Luna explore how AI algorithms are analyzing smartwatch sensor data to detect early signs of Lyme disease before symptoms appear. They dive into a 2025 study from the University of Colorado involving 1,200 participants, where the AI picked up subtle heart rate variability and sleep disruptions up to 48 hours before the classic bullseye rash. The conversation covers how continuous data from wearables like the Apple Watch and Fitbit is being repurposed for infectious disease surveillance, the privacy implications of sharing biometric data with researchers, and why this could be a game-changer for tick-borne illness in endemic regions like New England and the Upper Midwest. Lucas notes that the model's accuracy hit 87 percent in the study, with false positives mostly tied to other febrile illnesses. Luna questions whether the tech will widen health disparities if only smartwatch owners benefit. The hosts also touch on the role of citizen science apps like TickTracker in feeding data to the model, and what it means for the future of digital epidemiology.

#LymeDisease #SmartwatchAI #WearableHealth #DigitalEpidemiology #InfectiousDisease #HeartRateVariability #SleepTracking #AIHealthcare #UniversityOfColorado #AppleWatch #Fitbit #TickTracker #CitizenScience #PrivacyInTech #HealthTechPodcast #FexingoBusiness #BusinessPodcast #DigitalHealth

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In this episode of The Digital Health Podcast, Lucas and Luna explore how artificial intelligence is transforming dermatology by enabling early skin cancer detection from smartphone photos. They dive into the story of a 2025 study published in The Lancet Digital Health that tested an AI model trained on over 100,000 dermoscopic images. The model achieved 95% sensitivity for melanoma detection, matching board-certified dermatologists. The hosts discuss how this technology is being deployed in real-world apps like SkinVision and Miiskin, the regulatory hurdles at the FDA and CE marking, and the challenge of false positives. They also touch on the implications for teledermatology in underserved areas and the ethical questions around direct-to-consumer screening. Tune in for a focused look at how your phone camera might become a first-line diagnostic tool.

#AI #SkinCancer #Dermatology #MachineLearning #SmartphoneDiagnostics #Teledermatology #HealthcareAI #DigitalHealth #MelanomaDetection #TheLancet #SkinVision #Miiskin #FDA #MedicalDevice #HealthTech #Business #FexingoBusiness #BusinessPodcast

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Episode 112 dives into the emerging field of retinal imaging and AI: how a simple eye scan can now predict heart disease, Alzheimer's, and kidney failure before symptoms appear. Lucas breaks down the recent Nature study on retinal biomarkers, the startups racing to commercialize the tech, and why your optometrist might become your primary care gateway. Luna pushes back on data privacy concerns and access inequality. Specific numbers: the 81.6% accuracy for predicting cardiovascular events, the 500,000 retinal scans used to train the models, and the $6 billion market projected by 2030. A concrete look at how the window to the soul is becoming the window to your health.

#AI #RetinalImaging #DigitalHealth #PreventiveMedicine #EyeScan #NatureStudy #Alzheimers #HeartDisease #Biomarkers #Startups #HealthTech #Business #Technology #FexingoBusiness #BusinessPodcast #TheDigitalHealthPodcast #LucasAndLuna #EarlyDetection

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Lucas and Luna explore a new frontier in diagnostic AI: tongue analysis. Traditional Chinese Medicine has long used tongue observation, but now computer vision models are being trained to detect conditions from COVID-19 to pancreatic cancer by analyzing tongue color, coating, and texture. They dive into the specific research from the University of South Australia and Iraq that achieved 95% accuracy in detecting diabetes from a simple tongue photo. Lucas explains how the AI works, the cultural bridge between Eastern medicine and Western tech, and why smartphone-based tongue screening could be a powerful triage tool in underserved areas. Luna raises questions about standardization, privacy, and whether this will ever replace a blood test. A focused look at one of the most unexpected applications of AI in health.

#TongueAnalysis #AIDiagnostics #ComputerVision #TraditionalChineseMedicine #UniversityOfSouthAustralia #DigitalHealth #WearableTech #Telemedicine #DiabetesDetection #SmartphoneScreening #MedicalAI #TriageTool #HealthTech #Business #Technology #FexingoBusiness #BusinessPodcast #TheDigitalHealthPodcast

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Episode 110 of The Digital Health Podcast with Fexingo dives into the emerging field of non-invasive blood glucose estimation from wearable sensors. Lucas and Luna explore how researchers at the University of Washington and companies like Rockley Photonics are using optical sensors and machine learning to estimate glucose levels without needles. They break down the limitations of current continuous glucose monitors (CGMs) and explain how algorithms trained on heart rate variability, skin temperature, and accelerometer data can predict glucose spikes up to 30 minutes in advance. The episode highlights a 2025 study from Diabetes Technology & Therapeutics showing 85% accuracy compared to finger sticks, and discusses why this technology could change diabetes management for the 37 million Americans with diabetes. But they also caution that these models are not yet FDA-cleared and still face challenges with calibration across skin tones and activity levels. The hosts weigh the hype against the reality, and what it means for the future of metabolic health wearables.

#AI #BloodGlucose #Smartwatch #Wearables #Diabetes #MachineLearning #HealthTech #DigitalHealth #CGM #NonInvasive #RockleyPhotonics #UniversityOfWashington #MetabolicHealth #FitnessTracker #TechBusiness #BusinessPodcast #FexingoBusiness #TheDigitalHealthPodcast

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Episode 109 of The Digital Health Podcast with Fexingo explores how continuous glucose monitors, long confined to diabetes management, are becoming a mainstream health wearable for everyone. Lucas and Luna dive into the numbers: the global CGM market is projected to hit $20 billion by 2028, driven by companies like Abbott with its Libre 3 and Dexcom with the G7. They discuss the shift from prescription-only to over-the-counter availability, with the FDA's 2024 clearance of Abbott's Libre Rio for non-diabetic users. The hosts examine the science behind glucose tracking for metabolic health, citing research from Stanford's Snyder Lab showing personalized glucose responses to the same foods. They also touch on the controversy: critics argue CGMs create 'orthorexia' or unnecessary anxiety for healthy individuals. The episode includes a donation segment tied to listener support on Buy Me a Coffee.

#ContinuousGlucoseMonitor #CGM #Abbott #Dexcom #WearableTech #DigitalHealth #MetabolicHealth #GlucoseTracking #HealthTech #Business #Technology #FDA #Stanford #Insulin #Diabetes #Wearables #FexingoBusiness #BusinessPodcast

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In this episode, Lucas and Luna explore how smartwatch-based atrial fibrillation detection is moving from novelty to clinical standard. They focus on the Apple Heart Study published in the New England Journal of Medicine, which enrolled over 419,000 participants and used a smartwatch-based irregular rhythm notification algorithm. The conversation covers the study's key findings, including the positive predictive value of the algorithm, the rate of subsequent clinical diagnoses, and the implications for population-level screening. They also discuss how this model is being replicated by other wearable brands and the role of AI in reducing false positives and improving specificity. Lucas and Luna weigh the clinical promise against the ethical and practical challenges of widespread consumer screening—like anxiety, overdiagnosis, and health equity. No marketing fluff, just a grounded look at where the evidence stands as of mid-2026.

#AppleHeartStudy #AtrialFibrillation #Wearables #DigitalHealth #SmartwatchECG #Cardiology #IrregularRhythm #PopulationScreening #ClinicalResearch #NewEnglandJournalOfMedicine #AI #MachineLearning #HealthTech #PreventiveCare #RemoteMonitoring #Business #FexingoBusiness #BusinessPodcast

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Lucas and Luna explore the emerging field of AI-powered seizure prediction using consumer wearables. They focus on the work of Boston-based startup Seer Medical and its predictive algorithm that analyzes heart rate variability, electrodermal activity, and accelerometer data from devices like the Apple Watch and Fitbit. The episode details a 2025 study showing 85% sensitivity in forecasting seizures 30 minutes before onset, the challenges of false alarms, and how the technology is moving from clinical validation to consumer availability. Lucas explains the machine learning model's training on over 10,000 hours of labeled data, while Luna discusses the regulatory path and patient privacy concerns. A balanced look at a technology that could transform epilepsy management but still faces hurdles in accuracy and adoption.

#SeerMedical #Epilepsy #SeizurePrediction #Wearables #AppleWatch #Fitbit #MachineLearning #HealthcareAI #DigitalHealth #HeartRateVariability #ElectrodermalActivity #ClinicalValidation #FDA #PatientPrivacy #BusinessAndTechnology #FexingoBusiness #BusinessPodcast #HealthTech

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