Synapse
Transforming Healthcare, One Connection at a Time.
Created on 18th April 2025
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Synapse
Transforming Healthcare, One Connection at a Time.
The problem Synapse solves
Healthcare providers are often overwhelmed with routine inquiries, leading to longer response times for patients seeking medical guidance. Many non-emergency concerns can be addressed through automated assistance, reducing the burden on healthcare professionals while ensuring timely patient support.
Our solution is an AI-driven telephone assistant for medical websites that leverages NLP to:
Answer common health questions and provide preliminary guidance.
Triage symptoms to classify urgency levels and recommend appropriate actions.
Schedule appointments based on the severity of symptoms.
Store patient data securely and trigger automated medication reminders via calls when necessary.
Scrape relevant government and private healthcare schemes from the internet based on user requirements.
Analyze medical reports automatically to assist in preliminary diagnosis and consultations.
This system streamlines patient interactions, enhances accessibility, and optimizes healthcare workflow, allowing medical professionals to focus on critical cases while ensuring patients receive timely and informed care.
Challenges we ran into
During the development of our AI-driven telephone assistant, we encountered several challenges:
Real-time Speech Processing – Ensuring accurate speech-to-text and text-to-speech conversion with minimal latency, especially over Twilio WebSockets.
Medical NLP Accuracy – Fine-tuning Natural Language Processing (NLP) models to correctly interpret user queries and provide reliable medical responses.
Urgency Classification – Developing an effective symptom classification model that prioritizes patients correctly and minimizes false positives/negatives.
Data Security & Compliance – Implementing secure database storage for patient data while ensuring compliance with HIPAA and data privacy regulations.
Automated Report Analysis – Processing and extracting key insights from medical reports while maintaining accuracy across different formats.
Web Scraping Limitations – Efficiently scraping relevant healthcare schemes from the internet while avoiding issues like CAPTCHAs and dynamic content loading.
Seamless Appointment Scheduling – Integrating an automated appointment booking system that syncs with hospital/clinic databases and avoids scheduling conflicts.
Despite these challenges, our team successfully tackled them through rigorous testing, iterative improvements, and leveraging the right technologies to build a robust and efficient AI-powered solution.