GENE 231:
Artificial Intelligence
for Beginners
Instructors for this course:
Michael Snyder, PhD
Stanford W. Ascherman, MD, FACS, Professor in Genetics
Ronjon Nag, PhD
Adjunct Professor in Genetics, Stanford School of Medicine
Director, R42 Longevity Fund
Artem Trotsyuk, PhD
Principal, R42 Fund, Teaching Assistant, AI Ethics Postdoctoral Research Scholar, Stanford Center for Biomedical Ethics
How will AI help medicine? Could it harm us?
This course will provide a high-level overview of AI techniques.
- Through pre-built hands-on exercises, we will cover neural networks and their applicability to generative AI and large language models.
- We will also discuss the societal and ethical issues surrounding the real-world applications of AI.
- This course is healthcare oriented, looking at the intersection of AI and Genetics to analyze advances that could be made but also ethical questions that should be asked.
The course is designed to be accessible to many disciplines and there are no pre-requisites.
Winter 2024 Student Papers
Olivia Anderson, Anjali Narain, Abbey Roth
Potential Utility of AI in the Genetic Counseling Space
Yug Biren Shah, Veronica Augustina Bot, Blake Thomson
Augmenting the Patient – Clinician Encounter with AI: A Novel History – Taking Tool “SARA” (Symptom Assessment Resource Aid)
Kwamina Nyame , Rong Chi , a nd Emily Chen
Application of AI in Drug Discovery
Michelle Han, Laura Paola Gomezjurado Gonzalez, Yemisi Joseph
APPLICATIONS OF AI IN AGING PREVENTION
Jun W. Kim, Peter W. Kane
All models are wrong, some are explainable – e xplainable AI for deep learning models to analyze genomic data
Aditi Merchant, Aadhav Prabu, Ragav Manimaran, Michelle Tai
How AI Could Supercharge Drug Discovery
Amanda Meyer , Ethan Chen, and Y anzhe Li
Leveraging Artificial Intelligence in Cancer Detection: Insights from Skin and Breast Cancer
Sa Cai, Meagan Moyer, and Joel Naor
An Exploration of Explainable Artificial Intelligence in Healthcare and Life Sciences
A u s t i n K . M u r c h i s o n a n d Y a n d a n W a n g
Beyond Human Resources: Adapting to AI in the Tech and Biotech Workforce
Carolyn Bell, Rachel Porter, Marc Schlichting, Arnhildur Tomasdottir
Applying Few – Shot Learning to Variant Interpretation for Consumer Directed Genetic Data
Caroline Park, Corinn Sophia Small, Eirini V amva, Jianxiu Zhang
Using AI to match patients who suffer from generalized anxiety and depression with better diagnosis and medication
Slides
Xiaochen Xiong, Chenjie Pan, Ze Yang, Aybike Saglam
Use scGPT to study the development of Alzheimer’s disease
Claudia Zimmerman, Johanna V on Der Leyen, T amar Green, Shahar Lev Ari
The Role of AI in Medical and Envir onmental Disciplines