Morse fall Prevent Assistant

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  Morse Fall Assistant

Inspiration

Our primary inspiration for starting this project stemmed from a desire to drastically reduce patients' falling incidents. Falls can lead to serious injuries across all age groups, and patient falls in hospitals or nursing homes can have grave consequences. We recognized that these incidents are preventable and sought to improve fall prevention measures using the latest technology. This motivation inspired us to develop the 'Morse Fall Prevent Assistant.'

What it does

The Morse Fall Prevent Assistant is an app that allows users to assess and manage their fall risk. Users can evaluate their fall risk through a series of questions, and the app categorizes the risk level as low, moderate, or high. It provides preventive measures suitable for their risk level, helping users to improve their health status and prevent falls. Additionally, users can ask further questions through an integrated chatbot, enabling them to obtain information on fall prevention in real-time.

How we built it

Morse Fall Prevent Assistant was built upon generative AI models and prompt engineering. We trained AI models that could analyze users' responses and evaluate their fall risk, developing an algorithm that calculates risk scores using a fall assessment tool chart. The app’s chatbot feature was also designed using AI technology to respond to users' queries. Various project management and development tools were utilized throughout this process.

Challenges we ran into

The most challenging part of the project was creating AI models that could accurately process and understand responses from a diverse user base. Assessing fall risk can be highly subjective, and user responses can vary greatly. Providing accurate risk assessments and practical preventive measures based on the assessment tool also posed a challenge. To address these issues, we continually tuned our models and improved the system based on user feedback.

Accomplishments that we're proud of

Through the development of the Morse Fall Prevent Assistant, we were able to realize the potential of AI in the field of fall prevention for patients. We're particularly proud of receiving positive feedback from users for our user-friendly interface and accurate risk assessment functionality. Additionally, the project has significantly enhanced our team's collaboration and problem-solving skills through exploring effective uses of AI and prompt engineering.

What we learned

This project taught our team about the role and potential of AI in the field of fall prevention. We realized how useful AI technology can be in solving real societal problems, especially in the field of healthcare. We also learned about the importance of prioritizing user experience in app development and the methods of educating AI through prompt engineering.

What's next for Morse fall Prevent Assistant

The next steps for the Morse Fall Prevent Assistant involve enhancing the user experience and improving the app's accuracy and usefulness. We plan to refine the app's functionalities based on continuous feedback from users. Moreover, we aim to further develop the fall risk assessment feature and extend its applicability across different user environments, allowing a wider audience to benefit from fall prevention. Continuous efforts will also be made to improve the AI model's performance and the chatbot's conversational capabilities.

Built With

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