AI for Health Equity Symposium: Workshop Registration, AIM-AHEAD
Created by Katie Stinson
AI for Health Equity Symposium (AIHES) Workshop Registration Information You may register to attend all or some of the workshops in the series. Attendance for the hands-on portion of the workshop series is limited to 20 people and is first-come, first-serve for those who meet inclusion criteria. Check whether you qualify for priority registration here. Priority registration will be open through June 28th, and then registration will be open to everyone on June 28th for participation in the hands-on portion if there are openings. Although participation in the workshop is limited, anyone may sign up to watch/listen and engage through the Q&A. The Basics I (July 5th; 11:00 am - 2:00 pm CT) •Equity/disparities •SEDoH •What is AI/ML/data science/epi/statistics/computer science/data mining/ automation •AI use cases •Successes, challenges, and opportunities The Basics II (July 6th-7th; 11:00 am - 2:00 pm CT) •AI/ML - two camps •AI/ML examples •What to know about AI/ML & Health - complexity of health, large data/big data, common myths, prescription, prescription, association, causation •Software, Hardware & Infrastructure (including Cloud) Ethics in AI/ML (July 8; 12:00 pm - 2:00 pm CT) •What is ethics in AI/ML •Data ethics •Algorithm bias •Community participation All of Us Data & Data Browser (July 11; 1:00 pm - 3:00 pm CT) •How to access All of Us Data •Possibilities of All of Us Data Implementing AI/ML for health equity applications in low-resource settings (July 12-13; 2:00 pm - 4:00 pm CT) •Health equity disparities & inequities - definition and common terms (cloud, workbench, other infrastructure) •Operating systems/platforms (open source & proprietary) •What does an ideal AI/ML environment look like? •Working around for low-resource settings (requirements, data, IRB, infrastructure, internet issues, cloud, GPU, CPU) •How can I create my own low-cost infrastructure? (galaxy projects, using our laptop, connecting a couple desktops to create a server) •Players (systems architect, data scientist, statistician, content expert) •Software Conducting a project in AI/ML for health equity from start to finish in low-resources settings (July 14-15; 12:00 pm - 2:00 pm CT) •Research question •Data - challenges & troubleshooting •Model Building 101 (training/testing, model performance metrics, number of models, model selection, types of models, deep learning) •Execution in R or Python •Interpretation •Reporting AI/ML knowledge and communication for leadership in healthcare (July 18; 1:00 - 3:30 pm CT) ML methods with Healthcare Data (July 19; 12:00 pm - 2:00 pm CT) •Supervised Learning (classification, regression) •Unsupervised Learning •Interpretable AI/ML (SHAP Values) Tools for Deep Learning (DL) and understanding DL use cases in biomedicine & beyond (July 20-22; 11:00 am - 2:00 pm CT) •Use cases (music, images, voice, healthcare, and more) •Classification models - build and train Cutting edge AI/ML applications I (July 25; 2:00 pm - 4:00 pm CT) •SageMaker Clarify Cutting edge AI/ML applications II (July 26-28; 1:30 - 4:00 pm CT) •Voice-assisted technology, NLP, visual/optical technology Career Development (July 29; 2:00 pm - 4:30 pm CT) •How to build a competitive resume in AI/ML and healthcare •How to make your LinkedIn profile work for you •Interview advice -- how to answer content questions and come off as a professional in AI •How to network like a Rockstar
