Week 1: Brace yourself

Hi everyone! I’m Aadya, and I’m excited to kick off my first blog post. This week, I will be focusing on the applications of AI in medicine and how exactly machine learning can be used to simplify doctor-patient interactions. So, let’s dive into it!

Background and Introduction:

I was trying to schedule an appointment with my dentist and noticed that the website was last updated in 2002. This makes it difficult for patients to consult their dentist since patients must resort to calling the office if they want to schedule an appointment or address any concerns. When you need non-emergency immediate support, rather than waiting for a time when both the patient and doctor are available, patients can utilize an offline mode of communication to receive oral-care instructions that best suit their needs.

Additionally, according to the CDC, 65.5% of adults in America visited a dentist in 2019, which means that oral care is a heavily overlooked concern. Whether patients may not be able to find a dentist due to lack of availability or they simply cannot afford one, oral hygiene is incredibly important to prevent any diseases in the long term.

With my chatbot, patients will be able to receive immediate attention to resolve their issues in a timely manner. As a stretch goal, I hope to improve managing the doctor’s administrative tasks, such as schedule management. This would be beneficial to doctors since they are now able to keep track of patient history in a more efficient way. Therefore, through my chatbot, I will be able to help not only patients receive personalized care in a timely manner but also doctors, as they are often tasked with navigating countless files on patient data. This improves the dentist’s productivity, which allows them to address the needs of more patients.

Clinical Decision-Making with the Use of AI:

Currently, there is patient data that includes the patient’s medical history. As input, I will use a dataset that consists of patient history, medical records, and their stated problem. Using this information, the chatbot will be able to support the patient by providing oral-care tips or Over-The-Counter (OTC) medication if they are experiencing any pain. I plan on finding an EHR (electronic health record) system that would be beneficial to data acquisition as I will be equipped with large samples of data while ensuring patient privacy. These EHRs are HIPAA-compliant, so there would be no risk to both the patient and the doctor.

This application of Evidence-Based decision making uses neural networks to imitate how the human brain works in order to make clinical decisions similar to a dentist. In fact, machine learning helps dentists since it is able to learn from large samples of data to make accurate predictions. 

Conclusion:

My model will look at patients’ medical history and find the solution to the problem they are facing now. For example, if the patient had X issue in the past and they’re having dental issues now, the information I hope to find is how accurate the model can find the correlation between these problems and find a treatment to provide support. Using Large Language Models, my chatbot will find the best possible solution to improve oral hygiene without harming any past treatments/ surgery. Overall, my model should be able to provide personalized recommendations to improve the patient’s health. 

I hope to learn how to improve the accuracy of my model’s diagnoses and create a system with the support of medical professionals. By providing personalized assistance to patients, my algorithm will simplify doctor-patient interactions through immediate support.