AI for Remote Health Consultations

Small Language Models + Edge Technology = A New Era in #Healthcare AI is revolutionizing healthcare, but it’s not just about large-scale systems. Small Language Models (#SLMs) on edge devices—like smartphones, wearables, and IoT sensors—are creating real-time, cost-effective solutions that transform patient care. These lightweight, localized AI models operate independently of the cloud, ensuring speed, affordability, and security—even in areas with limited connectivity. Here are four powerful ways SLMs on edge devices are already shaping the future of healthcare: 1️⃣ MedAide: Real-Time Diagnostics on Edge Devices Built for low-latency performance, MedAide delivers diagnostic support in remote areas or during emergencies. Think high-quality healthcare anywhere—without relying on robust infrastructure. 2️⃣ CLAID: Unlocking Digital Biomarkers CLAID processes sensor data from wearables and smartphones, enabling real-time monitoring of health metrics (heart rate, oxygen levels, movement). It empowers precision medicine and early condition detection like never before. 3️⃣ Abridge: AI-Powered Medical Transcriptions By summarizing patient-doctor interactions in real time, Abridge saves doctors hours on documentation. Less admin work, more patient care. 4️⃣ AliveCor: AI-Driven Cardiac Monitoring Portable ECG devices that track and analyze heart health in real time. FDA-approved and built for proactive care—whether at home or on the go. Why SLMs on Edge Devices Matter • Speed: No cloud dependency = faster processing. • Cost-Effective: Affordable solutions for wide-scale deployment. • Privacy-First: Localized data processing enhances security. The Future is Now From rural clinics to urban hospitals, SLMs are bridging healthcare gaps, driving efficiency, and saving lives. 💡 Are you ready to integrate AI into your practice? Let’s discuss how small language models and edge tech can enhance workflows, improve care, and shape the future of medicine. #HealthcareInnovation #ArtificialIntelligence #EdgeComputing #HealthTech #DigitalTransformation #DrGPT

🚀 We just gave our doctors an AI twin at Dash Technologies—and patients love it. Hospitals run on razor-thin margins, so physicians are forced to sprint from room to room. The result? Burned-out doctors and patients who leave with more questions than answers. I saw it myself last Christmas: my cousin shattered his leg hanging holiday lights. Every follow-up visit lasted two rushed minutes, leaving him confused and frustrated. So we asked a radical question: What if a virtual clinician could spend unlimited time with every patient? 🛠️ How we built it 1. HeyGen Avatar – We recorded a short video of one of our physicians and turned it into a photorealistic, talking avatar. 2. RAG on Microsoft Azure AI Search – Behind the avatar sits a Retrieval-Augmented Generation pipeline filled with peer-reviewed guidelines, discharge instructions, and our hospital’s own care protocols. 3. Guardrails – System-curated sources and continuous human review keep hallucinations at bay. Much more to share on this. ✅ The impact (projected) - +10 minutes average Q&A time per patient - +27 % patient-satisfaction scores - ↓ Burnout—physicians now focus on complex cases instead of repeating routine explanations We’re not replacing doctors; we’re giving them a super-powered teammate who’s always available, consistent, and endlessly patient. Exploring AI in healthcare? Let’s connect—I’m happy to share what worked, what didn’t, and how we kept compliance & privacy front and center. #AI #HealthcareInnovation #DigitalHealth #PatientExperience #MicrosoftAzure #HeyGen #RAG #DashintoAI  Dash Technologies Inc. Deepak Raj Jay Patadiya Suyash Deo Tanha Shah Pavan Kalyan Asanapuram Sharat Hegde

🏠 The Future of Heart Failure Care: Bringing Treatment to the Patient’s Home 🚀 At #THT2025, I had the privilege of speaking about a critical shift in heart failure (HF) management—moving beyond episodic, hospital-based care to a patient-centered, home-based model. The reality is that our current system is unsustainable, with: 📊 1.1M HF hospital discharges & 1.3M ER visits annually 📈 $31B in HF-related costs, projected to hit $70B by 2030 👥 A 46% expected increase in HF patients by 2030 Why Home-Based Management? ✅ Reduce hospitalizations & readmissions, increase health days at home ✅ Ease the burden on care teams with streamlined workflows ✅ Leverage emerging digital & AI-driven tools for early intervention ✅ Addresses disparities in HF care access & outcomes, overcome inertia! Innovations Driving This Shift 🔹 Remote Monitoring & AI Algorithms Bioimpedance, ballistocardiograph, seismocardiography, phonocardiography, ECG, and other variables to identify congestion before it leads to hospitalization. 🔹Smartphone-based HF detection—improving accessibility & early intervention. 🔹 The “Hospital-at-Home” Model High-acuity care is delivered in the home through a 24/7 command center. Virtual visits + on-demand clinician dispatch to preserve continuity of care. FDA-collaborated remote tech enabling proactive, rather than reactive, HF care. By combining virtual management, predictive analytics, and AI-assisted triage, we can envision a future in which we drastically reduce hospital burden and improve patient outcomes. 🔹 What are your thoughts on the shift toward home-based HF care? 🔹 How can we scale these technologies while preserving health equity? #HeartFailure #DigitalHealth #AIinHealthcare #RemotePatientMonitoring #THT2025