Goals

The AI-Driven Healthcare Applications team focuses on developing AI technology that can perform a range of basic tasks, from detection and recognition of medical conditions to more intricate challenges such as segmentation. The team specializes in developing deep learning systems specifically tailored for embedded computer vision and various healthcare applications.

Issues Involved or Addressed

The project team’s research drive is centered around addressing a key question: How can we efficiently extract features from medical images using AI to achieve robust accuracy in real-time processing for a range of healthcare applications? This encompasses a diverse array of medical imaging modalities, including endoscopic image datasets, ultrasound, MRI, and CT datasets.

Methods and Tech

Through collaborations  with BIO5, the UA Cancer Center, University of Arizona Health Sciences, and other research units, the team works closely with clinicians who can provide relevant datasets.

Research and design methods include:

• AI modeling
• Machine learning
• Medical imaging
• Reinforcement learning from human feedback

Academic Majors of Interest

Open to all majors, including:

• Engineering (Electrical & Computer, Biomedical)
• Computer Science / Data Science
• iSchool
• STEM
• Honors College

Preferred Interests and Preparation

Preferred Skills:

• Ability to analyze data
• Attention to detail
• Documentation skills
• Familiarity with Excel, Python, C, and/or R

Preferred Attributes:

• Self-motivated and organized
• Interested in learning as well as mentoring peers

Application Process

To express interest in this team, please complete the VIP Interest Form and select "AI-Driven Healthcare Applications."

Team Advisor

Eung-Joo Lee, PhD