Pulse

An AI-powered healthcare application providing accessible and affordable services to users worldwide, especially in resource-constrained areas. Powered by Django, Scikit Learn, Tensorflow & GCP.

Comment

Inspiration

I am inspired by the challenges faced by the existing healthcare systems, particularly in resource-constrained areas. The struggle to provide timely and cost-effective solutions highlights the need for accessible and affordable healthcare services. These obstacles have led to a significant global health burden, accompanied by the following problems:

  1. One area that deeply concerns me is the prevalence of non-communicable diseases (NCDs) like cardiovascular diseases and diabetes. NCDs account for a staggering 71% of all deaths globally, making early detection crucial.
  2. Mental health disorders, affecting people of all ages, are another pressing issue that inspires me to take action. With around 1 in 4 individuals experiencing a mental health disorder in their lifetime, it's evident that the treatment gap is far-reaching.
  3. Additionally, the adverse effects of malnutrition, including undernutrition and micronutrient deficiencies, cannot be ignored. The toll it takes on health, cognitive development, and productivity urges me to seek ways to combat this issue effectively.
UN SDG Goals we are trying to solve:
  1. SDG 3: Good Health & Wellbeing
  2. SDG 2: Zero Hunger
Targets (UN SDG INDICATOR) :
  1. 3.4.1: Mortality rate attributed to NCD’s
  2. 3.4.1: Promote mental health & Wellbeing
  3. 3.8.1: Coverage of essential health services
  4. 2.1.1: Prevalence of undernourishment

What it does

Feature Feature Description
Non Communicable Diseases (NCD) Diagnosis Pulse incorporates Random Forest algorithm from Scikit-learn to predict the occurrence of NCDs like cardiovascular diseases, diabetes, liver disease, and brain tumors. With an impressive accuracy of 90%, Pulse enables early detection and accurate diagnosis, leading to improved health outcomes.
Personalized Nutrition for Optimal Health Pulse's diet planner is an innovative feature designed to provide personalized and AI-driven meal plans. It leverages advanced algorithms and machine learning techniques, including Random Forest from Scikit-learn, to create customized diet plans tailored to individual needs and goals. The diet planner takes into account various factors, including an individual's age, gender, weight, height, activity level, dietary preferences, and any specific dietary requirements or restrictions.
Mental Health Pulse's mental health tool is powered by TensorFlow, a deep learning framework. It goes beyond diagnosis and prediction by providing users with a comprehensive mental health score and valuable suggestions for support. By leveraging TensorFlow's capabilities, Pulse analyzes input data related to behavioral patterns, symptoms, and other factors to generate an individual's mental health score. In addition to the mental health score, Pulse's tool utilizes Google Cloud SQL to fetch a curated set of suggestions and helpline information.
Medical Profile Maintenance By allowing users to maintain their comprehensive medical profiles, Pulse ensures that essential health information is easily accessible and securely stored. This feature addresses the problem of limited accessibility to medical records, especially in resource-constrained areas.
Analysis of Diagnosis History Pulse's capability to analyze diagnosis history provides valuable insights into an individual's health journey. This feature allows users and healthcare professionals to track progress, identify patterns, and make informed decisions regarding treatment and interventions.
Access to Informative Blogs Pulse's provision of informative blogs offers a valuable resource for individuals seeking information and guidance on various health topics. This feature helps address the problem of limited access to reliable health information, empowering users to make informed decisions about their health and well-being.

How we built it

  • Backend Development
    Web Framework: Django Framework, Python
    Database: SQLite (Local), MySQL (Production)

  • Frontend Development
    Languages: HTML, CSS, JQuery, JavaScript, Bootstrap

  • AI and Machine Learning
    TensorFlow, Scikit-Learn, Random Forest Classifier, Random Forest Regressor, Gradient Boosting Classifier, Gradient Boosting Regressor, Support Vector Machine, Pandas, NumPy, Seaborn, Matplotlib, Joblib

  • Google Cloud Platform
    Cloud SQL for Database
    Google App Engine: Deployment Server
    Cloud Storage: Hosting Static & Media Files, Machine Learning Models

Architecture

Challenges we ran into

Challenge Challenge Description Resolution
Deployment During deployment, we encountered a challenge with the Cloud SQL Database. Switched to Google Cloud SQL database for production.
Django's default SQLite database was not compatible with GCP. Configured the database with minimal settings to avoid excessive cost overheads.
After a day of deployment, we noticed cloud credits being used at an alarming rate due to default configurations. Researched alternative solutions to optimize Cloud SQL usage and manage costs efficiently.
Learned valuable lessons on how to handle Cloud SQL for future deployments.
AI Integration Integrating AI models into the application posed challenges. Serialized each model as an object to optimize backend response times.
Using heavy models in the backend led to longer response times. Stored serialized models in Google Cloud Storage to reuse them without repetitive retraining.
Achieved seamless integration of multiple AI models, maintaining optimal performance and accuracy.

Accomplishments that we're proud of

  • Comprehensive Healthcare Solution: Pulse's approach facilitates precise diagnoses and offers a one-step solution for both healthcare experts and common users, enabling efficient and accurate healthcare services.
  • High Diagnosis Accuracy: Pulse's tools achieved an average diagnosis accuracy of 90%, ensuring reliable and dependable results for medical practitioners and users.
  • Successful Implementation and Deployment: The project was successfully implemented and deployed, showcasing Pulse's commitment to excellence and a seamless user experience. Pulse underwent rigorous manual testing, ensuring the platform meets the highest standards of performance, usability, and security.

What we learned

Through this exhilarating project journey with Pulse, I have embarked on a transformative learning experience. As I delved into the challenges faced by the existing healthcare systems, I gained a profound understanding of the importance of accessible and affordable healthcare services, particularly in resource-constrained areas. The pursuit of solutions for the global health burden ignited a fire of inspiration within me, driving me to make a positive impact in the lives of millions.

Throughout this electrifying venture, I harnessed cutting-edge technologies like AI and machine learning, exploring the capabilities of tools such as Random Forest and TensorFlow. My mastery of these advanced techniques enabled me to achieve an astounding 90% average diagnosis accuracy, revolutionizing healthcare diagnostics and empowering medical professionals and users alike. This electrifying project has transformed me into a healthcare hero, an inspiration to others, and a beacon of hope in the quest for a healthier, happier world.

What's next for Pulse

  1. Partnerships with Healthcare Providers: Collaborate with hospitals and medical organizations to integrate Pulse's platform into their systems. This enables healthcare professionals to recommend and use Pulse for diagnosis, treatment, and patient engagement.
  2. Collaboration with Government and NGOs: Engage with healthcare-focused government agencies and NGOs to leverage their networks and resources. Facilitate the adoption of Pulse in public healthcare systems through public-private partnerships.
  3. Multi-language Support: Provide language options for users to access Pulse's features and content in their preferred language, enhancing inclusivity and accessibility.
  4. Data Privacy and Security: Implement robust encryption techniques and comply with data protection regulations. Regularly audit the platform's security infrastructure to safeguard user data.
  5. Blockchain-Based Identity Verification: Incorporate blockchain-based identity verification for enhanced user authentication and fraud prevention.

Built With

Share this project:

Updates