LLM enhanced Medical Notes

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Created by team fritzlabs on October 14, 2023

Working with medical notes puts a significant strain on healthcare professionals. The volume of findings is constantly increasing, driven by advances in medical technology and an aging population. These notes encompass a wide range of information, including clinical assessments, treatment plans, diagnostic test results, and progress reports. Navigating through this wealth of data demands meticulous attention and consumes valuable time that could be allocated to direct patient care. Medical findings are extensive, diverse, and complex, reflecting the intricacies of human health and the multifaceted nature of medical conditions. The diversity poses a challenge for healthcare workers, who must assimilate and synthesize this information to provide the best possible care. As a result, healthcare professionals spend a significant amount of time searching through these findings. They meticulously comb through records, striving to extract the most relevant information while ensuring nothing critical is overlooked. Yet, despite their best efforts, the sheer volume and complexity of medical notes can lead to instances where crucial details may inadvertently go unnoticed. This is where large language models step in as powerful tools to augment healthcare workflows. With their ability to rapidly process and comprehend vast amounts of text, they can swiftly analyze medical notes and extract pertinent information. By doing so, they assist in streamlining the information retrieval process, allowing healthcare professionals to allocate more time to direct patient interactions and clinical decision-making.

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"it is very helpful idea for doctors, but what happens when you ask your bot, how it can find the answer, it wasn't shown on your demo. your presentation is excellent, but needed more focus on problem and solution. plus about medical note is it made by AI when doctor fill it, or is it just example of EHR already available in hospital. your demo is silent, it would be better if you explain it while it is working. keep working on this project. it has a high business value when it is finished. good luck "


Walaa Nasr Elghitany

Data scientist and doctor

"Good initiative, using AI to evaluate the medical reports would be helpful and release the workload. I'm more curious about how it overlooks the file. I think you had to explain it in the presentation and elaborate on your future work to make it more productive because I faced errors while running my files. However, It's a good concept. Work on it"


Muhammad Mubashir Hassan


"The application has potential to clean data and save time. Further experimental results could showcase the benefit of your application. The presentation could help visualize the problem and potential solution."


Ervin Moore

PhD Computer Science Student