An AI-first sleep improvement app that combines advanced algorithms with IoT devices to address issues like insomnia, early waking, and disrupted sleep.
AI models analyze sound detection (snoring, sleep talking, ambient noise) and a 2-week sleep diary to provide personalized insights, dream analysis, and tailored recommendations.
IoT integration with smart masks and wearables (Apple/Android watches) tracks SpO? in real time, triggering vibration alerts to prevent oxygen drops and support early OSA intervention.
Users can connect with sleep experts via AI-enabled chat, audio, and video, while providers manage appointments and communications through a dedicated web interface.
The platform follows a subscription model with free and premium tiers, enabling sleep diagnostic centers to deliver AI-driven insights, IoT monitoring, and expert support for better sleep health.

The objective of proposed application is to enhance the management of chronic care disease by facilitating comprehensive data collection, treatment adherence, and patient-provider communication. The application aims to address the current lack of real-world data and studies in urology. It enables healthcare providers to monitor patient-reported symptoms, track pain trends, and assess treatment efficac Doctors can access a dashboard displaying all  patients, prioritize cases based on symptom severity, and receive alerts for critical cases. Patients can easily log symptoms, monitor their  scores, and receive reminders for medications and lifestyle changes, ensuring better adherence to treatment plans. It enables secure messaging between patients and providers, allowing for timely updates, treatment adjustments, and symptom reports. Patients can access personalized educational materials, including multimedia resources and chatbot support, to manage their condition effectively. The platform aims to deliver personalized, data-driven care, improve patient outcomes, and contribute valuable real-world evidence to further research and understanding of the problem

In this Project we use the Open Dental API to pull and display appointments in existing C# web application as well as syncing patient demographics and insurance payer information into Open Dental using its FHIR APIs helping eliminate the need for manual data entry by billing staff.