Headshot portrait of Akshay Jaggi - Bio-X Undergraduate Fellow
2017 Undergraduate Summer Research Program Participant

Home Department: undeclared
Supported by: Bio-X
Mentor: Sandy Napel, Radiology

When will computer vision surpass human vision? It’s happening right now: at Google, at Tesla, and right here at Stanford Bio-X. Using novel machine learning algorithms, Akshay is training computers to determine the malignancy of indeterminate lung tumors. Currently, radiologists cannot accurately classify these nodules, but, by going beyond human vision, these algorithms will aid doctors in making crucial clinical decisions.

Poster presented at the Stanford Bio-X Interdisciplinary Initiatives Symposium on August 24, 2017:

Robust Cancer Image Feature Discovery through Novel Digital Phantoms

Akshay Jaggi1, Sebastian Echergay1, Shaimaa Bakr2, Sandy Napel1
[Departments of Radiology1 and Electrical Engineering2, Stanford University]