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

Lucas and Luna explore how hospitals are using AI to predict bed occupancy hours and days in advance, reducing emergency department boarding and surgical delays. They dig into real-world deployments at NYU Langone and Tampa General, where predictive models trained on admission, discharge, and transfer data have cut ambulance diversion by 40% and improved OR start times. The hosts discuss the data...

In this episode of Healthtech Talks with Fexingo, Lucas and Luna explore how artificial intelligence is being used to predict which patients are likely to miss their appointments—and what hospitals are doing about it. They dive into a specific case: how the University of Pittsburgh Medical Center reduced no-show rates by 30 percent using a machine learning model that factors in over 200 variables,...

Episode 52 of Healthtech Talks digs into one of the most stubborn operational headaches in healthcare: operating room scheduling. Lucas and Luna explore how Northwestern Memorial Hospital in Chicago used machine learning to cut unused OR time by 18% in 2025, saving $4.2 million annually. They walk through the specific model—a gradient-boosted decision tree trained on case duration, surgeon prefere...

Medication errors in U.S. hospitals cause an estimated 250,000 adverse drug events each year. In this episode, we look at how AI-powered clinical decision support systems are intercepting dosing mistakes before they reach patients. Lucas and Luna discuss a specific case from a 400-bed hospital where natural language processing and real-time drug interaction checks reduced error rates by 44%. They...

Every year, nearly 80% of clinical trials fail to enroll enough patients on time. In this episode, Lucas and Luna explore how AI-powered platforms are changing that — screening electronic health records, matching patients to trials in minutes instead of weeks, and even predicting which trials a specific patient is most likely to complete. They break down the numbers behind trial matching, look at...

In this episode of Healthtech Talks, Lucas and Luna explore how artificial intelligence is being deployed to detect lung cancer earlier and more accurately from low-dose CT scans. They focus on a specific 2024 study from the Journal of Clinical Oncology that found AI screening reduced false positives by 40 percent compared to radiologist-only reads. The hosts break down the numbers: the 10,000-pat...

Healthcare billing is a $400 billion industry burdened by manual coding errors that cost hospitals billions in denied claims. In this episode, Lucas and Luna explore how AI-driven medical coding assistants are transforming revenue cycle management. They take us inside a pilot program at a mid-sized hospital system where an AI model reduced claim denials by 30 percent and cut coding time in half. T...

In this episode of Healthtech Talks, hosts Lucas and Luna explore how artificial intelligence is not just reading medical images but actually decoding the unstructured text in radiology reports to accelerate diagnosis and treatment. They examine the case of a major academic medical center that deployed natural language processing to extract critical findings like pulmonary embolisms and incidental...

In this episode of Healthtech Talks, Lucas and Luna explore how artificial intelligence is transforming emergency department triage and patient flow. They focus on a specific case: the deployment of an AI-powered triage tool at a major urban hospital in Chicago that reduced average ED wait times from 4.5 hours to just over 2 hours within six months. Lucas explains how the system works — using natu...

Episode 45 of Healthtech Talks with Fexingo. Lucas and Luna dive into a new wave of AI models that can predict which patients are likely to be readmitted to the hospital within 30 days of discharge — and do it in under 24 hours after admission. They examine a recent study from Mount Sinai Health System in New York, where a deep-learning algorithm trained on electronic health record data achieved a...

Sepsis kills one in five people worldwide, but AI models can now spot it hours before traditional warning signs appear. Lucas and Luna explore how a system called the Sepsis Early Detection Algorithm (SEDA), deployed at a major U.S. hospital network, analyzes real-time vitals and lab results to flag at-risk patients. They walk through a concrete case: a 68-year-old post-surgery patient whose heart...

More than one million patient falls occur in U.S. hospitals each year, leading to fractures, longer stays, and liability costs exceeding $50 billion annually. Traditional risk scores like the Morse scale rely on manual assessments that miss 40% of fallers. In this episode, Lucas and Luna examine how Mount Sinai and Stanford Medicine are deploying computer vision and electronic health record algori...

In this episode of Healthtech Talks, Lucas and Luna explore the quiet revolution of AI-powered ambient clinical documentation. They focus on Nuance's DAX Copilot, which listens to doctor-patient conversations and automatically generates structured medical notes. Lucas reveals that DAX is now used by over 500,000 clinicians, saving them an average of two hours per day on charting. Luna highlights t...

In this episode of Healthtech Talks, Lucas and Luna explore how ambient AI transcription is quietly transforming the doctor-patient relationship. Rather than typing notes during appointments, physicians at Mayo Clinic and other health systems now use tools that listen, summarize, and structure clinical documentation automatically. The hosts discuss the specific workflow changes at Mayo, the 50 per...

Lucas and Luna dive into the world of AI-enhanced surgical robotics, focusing on how Intuitive Surgical is integrating machine learning into its da Vinci systems. They explore a specific case: a partnership between Intuitive and NVIDIA to embed real-time AI that helps surgeons avoid critical structures like blood vessels during robotic-assisted procedures. Lucas breaks down the technology, the reg...

Lucas and Luna explore how artificial intelligence is analyzing routine cardiac CT scans to detect hidden plaque and predict heart attacks years in advance. They focus on a landmark study from 2025 showing that an AI model trained on over 20,000 scans identified high-risk patients 30 percent more accurately than traditional risk scores. The hosts discuss how the tool, developed by researchers at O...

Episode 38 of Healthtech Talks with Fexingo examines how artificial intelligence is transforming patient monitoring in hospitals. Lucas and Luna dive into the story of a pilot program at Johns Hopkins that used AI to predict patient deterioration hours before traditional vital sign thresholds would trigger alarms. They discuss the shift from reactive to proactive monitoring, the role of wearable s...

Episode 37 of Healthtech Talks explores how machine learning models are being deployed in hospital microbiology labs to identify drug-resistant infections faster than traditional culture tests. Lucas and Luna discuss a specific algorithm developed at the University of Pittsburgh Medical Center that analyzes bacterial DNA sequences and predicts antibiotic susceptibility in under two hours, compared...

Episode 36 of Healthtech Talks with Fexingo breaks down how artificial intelligence is transforming hospital supply chains. Lucas and Luna explore a real case: a 400-bed hospital in Ohio that used AI to reduce supply waste by 18% and cut stockouts by 40% in six months. They discuss the role of predictive algorithms, real-time inventory tracking, and the shift from just-in-time to just-in-case mode...

Every year millions of chest X-rays are performed for reasons unrelated to bone health — pre-op clearance, pneumonia checks, routine physicals. But a hidden signal is sitting in those images: bone density. In this episode, Lucas and Luna explore how radiologists at Mass General Brigham trained an AI model to flag osteoporosis from chest X-rays taken for other purposes, achieving 87 percent accurac...

This episode of Healthtech Talks explores how artificial intelligence is transforming diabetic retinopathy screening. Every year, millions of people with diabetes risk blindness because eye exams are too expensive, too scarce, or too late. Lucas and Luna focus on IDx-DR, the first FDA-authorized AI system that can diagnose diabetic retinopathy from a retinal photo without a specialist present. The...

Lucas and Luna explore a new wave of predictive AI in neurology: machine learning models that analyze brain scans, speech patterns, and electronic health records to flag Alzheimer's risk up to seven years before clinical symptoms emerge. They examine a specific 2025 study from Mass General Brigham that trained a deep learning model on over 200,000 brain PET scans, achieving 92% accuracy in predict...

In this episode of Healthtech Talks with Fexingo, Lucas and Luna dive into the emerging field of vocal biomarkers for mental health diagnosis. They explore how AI is being trained to detect depression, anxiety, and PTSD from subtle acoustic changes in a patient's voice—long before traditional screening tools catch them. The discussion centers on a real-world deployment at a major academic medical...

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 detecti...

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 frict...