An image showing a healthcare professional using a tablet, indicating the use of advanced technology in healthcare such as Chatbots.

CareCounselor: A Chatbot for Disease Management Support

Company Information

The Challenge

The Results

Portfolio Management

Analyzed the current document parsing options and improved on them, ensuring the chatbot is provided with the most accurate information.

Identified that the generative model had a significant performance decrease when dealing with low-resource languages. To improve on this, we have developed a custom solution to translate from the user input language to English, ensuring the model can perform at its best.

Patient segmentation was achieved by adding an NLP layer that would categorize the user. The segment is then used to adjust the chatbot tone, creating engaging interactions.

Developed the project in AWS Sagemaker ensuring flexibility and easing client deployment.

Added a custom localization tool, ensuring that users could ask the chatbot for directions around their neighborhood to find pharmacies, clinics and hospitals.

Fine-tuned the embedding model used to power a Retrieval-Augmented Generation system and tracked the performance results on Sagemaker Experiments.

Conclusion

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