Faculty Partner: Dr. Thanujaa Subramaniam

Fellows: Dave Song & Peter Graham

Context

With Dr. Subramaniam and Peter, I researched and identified the gap between the increasing technical demands of recent clinical research implementations and the technical knowledge of junior investigators and clinicians. Despite collaborations between data science experts and researchers, many clinicians lack the technical background or knowledge to fact-check or critically analyze the research implementation details to see if the implementation and development are done properly. To resolve this, I worked with Peter and Dr. Subramaniam under Dr.Clark's supervision to develop an interactive curriculum for investigators at Brown University’s Warren Alpert Medical School to cover the fundamental skills required to actively participate in and evaluate clinical research involving a heavy technical portion ranging from data science to machine learning and artificial intelligence.

Conference Learning Outcome 

1. Use Python to successfully import, export, and manipulate data.

2. Match appropriate statistical methods to different data types, ensuring that conclusions drawn from the data are valid, reliable, and suitable for making informed decisions in a clinical context.

3. Understand data science as an interdisciplinary field that combines programming, statistics, and visualization. Consider your own role and contributions within data science as a clinical researcher.

4. Understand the inner workings of fundamental AI and ML algorithms, as well as their strengths and weaknesses, to effectively select appropriate models and algorithms suited for research datasets and goals.

5. Gain high-level knowledge of advanced AI models and algorithms to stay informed about current topics discussed in Data Science and Computer Science communities, enhancing collaborative efforts between clinical researchers and data science professionals.

6. Identify ethical challenges related to handling medical data, particularly in AI applications. Develop strategies to ensure responsible data governance, inclusivity, and ethical practices in medical research.

Full Program Syllabus: Here (Please use your brown email)