Healthtech Talks with Fexingo: Digital Health, Telemedicine, and Medical Software

In this episode of Healthtech Talks, Lucas and Luna explore how deep learning models are now diagnosing skin cancer from smartphone photos with accuracy rivaling board-certified dermatologists. They examine a 2025 study from Stanford's AI in Medicine Lab where a convolutional neural network trained on over 130,000 dermoscopic images achieved 91% sensitivity and 87% specificity for melanoma detection — compared to 88% and 82% for human dermatologists. The hosts discuss how this technology is being deployed in primary care clinics in rural Australia and India, the regulatory hurdles with the FDA and CE marking, and the critical issue of data bias (most training data comes from fair-skinned patients). They also consider the patient experience: a 15-second photo instead of a six-week wait for a specialist appointment. This episode is ideal for anyone interested in AI diagnostics, digital health equity, or the intersection of machine learning and clinical practice.

#SkinCancer #AI #DeepLearning #Telemedicine #Dermatology #Stanford #FDA #HealthEquity #PrimaryCare #Melanoma #DiagnosticAI #RuralHealth #SmartphoneDiagnosis #MedicalImaging #CNN #DigitalHealth #FexingoBusiness #BusinessPodcast

Keep every episode free: buymeacoffee.com/fexingo

Emergency rooms across the US are testing AI-driven triage systems that predict patient acuity and wait times in real time. Lucas and Luna examine the case of UC San Diego Health, where an AI triage tool reduced average ER length of stay by 12 percent in its first year. They discuss how the model works—using vital signs, chief complaints, and historical data to assign severity scores—and the friction it creates with clinicians accustomed to their own judgment. The episode also explores equity concerns: does the AI under-triage certain demographics? And what happens when the algorithm is wrong? A grounded look at one of healthtech's most consequential deployments.

#AI #Healthtech #ERTriage #UCSanDiegoHealth #ArtificialIntelligence #EmergencyMedicine #ClinicalDecisionSupport #WaitTimes #PatientOutcomes #MachineLearning #HealthEquity #HospitalOperations #DigitalHealth #MedicalSoftware #PredictiveAnalytics #Triaging #Business #FexingoBusiness

Keep every episode free: buymeacoffee.com/fexingo

Episode 29 of Healthtech Talks explores how artificial intelligence is analyzing data from consumer wearables like the Apple Watch to detect atrial fibrillation and other heart conditions before symptoms appear. Lucas and Luna discuss a landmark study from the Stanford Digital Health Lab showing that AI models trained on photoplethysmography data can identify irregular heart rhythms with 98 percent sensitivity. They break down how the technology works, where it still falls short (including false positives and demographic bias), and what it means for the future of preventive cardiology. The episode also touches on FDA clearance pathways for software-as-a-medical-device and the role of telehealth in follow-up care. No hype, just the signals that matter.

#AppleWatch #AtrialFibrillation #AIinHealthcare #WearableTech #DigitalHealth #Cardiology #StanfordDigitalHealth #Photoplethysmography #FDA #SaMD #PreventiveMedicine #MachineLearning #Telehealth #Healthtech #Business #FexingoBusiness #BusinessPodcast #HealthtechTalks

Keep every episode free: buymeacoffee.com/fexingo

In this episode of Healthtech Talks, Lucas and Luna explore how artificial intelligence is being used to personalize cancer treatment. They focus on a specific case: Memorial Sloan Kettering Cancer Center's use of an AI system called Watson for Genomics to analyze tumor DNA and recommend targeted therapies. The hosts discuss how the system works, the real-world impact on patient outcomes, and the challenges of integrating AI into oncology workflows. They also touch on the broader shift toward precision oncology and how other institutions like the Mayo Clinic are following suit. The conversation covers the technology behind AI-driven genomic analysis, the data infrastructure required, and the ethical considerations around algorithm-driven treatment decisions. By the end, listeners will understand how AI is helping oncologists move from one-size-fits-all protocols to tailored treatment plans based on a patient's unique genetic profile.

#AI #PrecisionOncology #CancerTreatment #MemorialSloanKettering #WatsonForGenomics #GenomicAnalysis #TargetedTherapy #Healthtech #ArtificialIntelligence #Oncology #MayoClinic #ClinicalDecisionSupport #PersonalizedMedicine #Business #Technology #FexingoBusiness #BusinessPodcast #HealthtechTalks

Keep every episode free: buymeacoffee.com/fexingo

Medication errors harm over 1.5 million patients in the US each year. In this episode, Lucas and Luna explore how artificial intelligence is being deployed in hospital pharmacies to catch dangerous drug interactions, dosage mistakes, and allergy conflicts before they reach the patient. They focus on a specific case: the implementation of AI-driven clinical decision support at the University of California San Francisco (UCSF) Medical Center, where machine learning models cross-reference patient records in real time. Lucas breaks down the technology—how natural language processing reads physician orders and how predictive algorithms flag high-risk combinations. Luna questions the false-positive problem and whether AI can truly replace a pharmacist's judgment. The conversation also touches on the challenges of integrating AI with existing electronic health record systems and the regulatory landscape. By the end, listeners understand both the life-saving potential and the current limitations of AI in medication safety.

#MedicationErrors #PatientSafety #AI #ClinicalDecisionSupport #UCSF #HospitalPharmacy #NaturalLanguageProcessing #MachineLearning #HealthcareAI #DrugInteractions #ElectronicHealthRecords #Pharmacy #HealthIT #MedicalErrors #PredictiveAnalytics #Business #FexingoBusiness #BusinessPodcast

Keep every episode free: buymeacoffee.com/fexingo

Episode 26 of Healthtech Talks with Fexingo explores how artificial intelligence is transforming medical coding — the process of translating patient encounters into standardized billing codes. Lucas and Luna break down why this once-obscure back-office task is suddenly attracting venture capital and causing controversy among coders. They explore a specific case: a mid-sized hospital system that used an AI coder to reduce claim denials by 22 percent in six months, saving $3.2 million annually. The hosts also discuss the human cost: how many coding jobs could be displaced, and what the American Medical Association's new guidelines mean for AI adoption. This episode offers a concrete look at a quiet revolution in healthcare administration that directly impacts hospital revenues and patient billing.

#AI #MedicalCoding #Healthtech #RevenueCycleManagement #Nuance #EpicSystems #AMA #Business #Technology #Healthcare #Automation #ClaimsDenial #HospitalFinance #CodingJobs #ICD10 #FexingoBusiness #BusinessPodcast #HealthtechTalks

Keep every episode free: buymeacoffee.com/fexingo

Hospitals spend over $40 billion annually fighting healthcare-associated infections (HAIs). In this episode, Lucas and Luna examine how AI-powered infection surveillance systems are catching outbreaks hours or days before traditional methods. They walk through a real case at a 500-bed hospital in Pennsylvania where a machine learning model predicted a C. diff cluster 48 hours before any patient showed symptoms — and how the system cut infection rates by 34 percent in six months. They also discuss the challenges: data integration with legacy electronic health records, alert fatigue among infection preventionists, and whether hospitals will actually invest in prevention versus treatment. No hype — just a grounded look at one of healthtech's most quietly impactful use cases.

#AI #InfectionControl #HAI #Cdiff #MachineLearning #Healthtech #HospitalSafety #PredictiveAnalytics #EHR #InfectionPrevention #PatientSafety #ClinicalAI #HealthcareTechnology #Business #Technology #FexingoBusiness #BusinessPodcast #HealthtechTalks

Keep every episode free: buymeacoffee.com/fexingo

Episode 24 of Healthtech Talks explores how hospitals are using predictive AI to tackle the costly problem of missed appointments. Lucas and Luna break down the data behind no-show rates — which can hit 30 percent in some clinics — and how machine learning models analyze patient history, weather, and even commute distance to identify high-risk no-shows before they happen. They discuss real-world results from systems at Vanderbilt University Medical Center and a pilot at Boston Medical Center that cut no-shows by 22 percent. The hosts also tackle the tricky balance between nudging patients and respecting privacy, and why overbooking based on AI predictions can backfire. Specific numbers, a concrete case study, and no filler — just what operators and builders in healthtech need to know.

#PredictiveAnalytics #NoShowRates #HealthcareAI #PatientEngagement #Vanderbilt #BostonMedicalCenter #MachineLearning #AppointmentScheduling #OperationalEfficiency #Healthtech #HospitalAdministration #PatientCare #DataScience #BusinessPodcast #FexingoBusiness #HealthtechTalks #DigitalHealth #Podcast

Keep every episode free: buymeacoffee.com/fexingo

Episode 23 of Healthtech Talks with Fexingo dives into the hidden inefficiencies of hospital operating rooms, where underutilized OR time costs the U.S. healthcare system an estimated $25 billion annually. Lucas and Luna explore how AI-powered scheduling platforms—like those from LeanTaaS and Qventus—are using machine learning to predict surgical durations, reduce room turnover times, and boost OR utilization from 60% to over 85%. They discuss real-world results at major hospitals, including how one health system added 4,000 extra surgeries per year without new infrastructure. The conversation also touches on the challenges of integrating AI into legacy hospital IT systems and the human factor of surgeon resistance. A concrete look at how operational AI is making surgery more accessible and cost-effective.

#AI #ArtificialIntelligence #HealthTech #HospitalOperations #OperatingRoom #Surgery #PredictiveAnalytics #LeanTaaS #Qventus #MachineLearning #HealthcareEfficiency #OROptimization #DigitalHealth #Business #Technology #FexingoBusiness #BusinessPodcast #HealthtechTalks

Keep every episode free: buymeacoffee.com/fexingo

Discharge planning is one of the most chaotic processes in hospitals — delays cost billions and hurt patient outcomes. In this episode, Lucas and Luna explore how a handful of health systems are deploying AI to predict discharge dates, coordinate care teams, and reduce readmissions. They focus on the experience at Boston Medical Center, which piloted an AI model that cut average discharge time by nearly a full day and lowered 30-day readmission rates for high-risk patients. The conversation digs into the algorithms behind the tool, the data-sharing hurdles with nursing and social work staff, and why hospitals are slow to adopt even proven efficiency tools. Lucas brings the numbers: a typical 500-bed hospital loses roughly $3 million a year in revenue due to discharge delays alone. Luna pushes back on whether AI can truly account for social factors like housing or family support. The episode ends with a look at what it would take to scale these systems nationwide.

#AI #HospitalDischarge #HealthTech #BostonMedicalCenter #ReadmissionRates #PatientFlow #PredictiveAnalytics #ClinicalEfficiency #DigitalHealth #Business #Technology #FexingoBusiness #BusinessPodcast #HealthIT #CareCoordination #MachineLearning #HospitalOperations #RevenueCycle

Keep every episode free: buymeacoffee.com/fexingo