Apply here for the AI in Critical Care Boot Camp
Application Deadline: January 21, 2023. Event: April 19, 2023
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AI in Critical Care Bootcamp, Lake Nona, FL
$1,000 Travel Grants for Medical AI Bootcamp:
Application Instructions
The NIH Bridge2AI program “A Patient-Focused Collaborative Hospital Repository Uniting Standards for Equitable AI” (CHoRUS) is pleased to accept applications for travel grants of $1,000 each for medical staff or students at CHoRUS sites to attend the one-day AI in Clinical Care bootcamp in Lake Nona, Florida, on Wednesday, April 19, 2023.
The Grant
Up to 10 individuals will be awarded travel grants of $1,000 for costs related to attending the one-day medical AI bootcamp in Lake Nona, Florida, on April 19, 2023. The funds may be used to cover admission to the AI in Clinical Care bootcamp, travel to and from Lake Nona, accommodations, food, and other expenses related to attending the event at the following address:
UF Research and Academic Center at Lake Nona Campus
6550 Sanger Road
Orlando, FL 32827
Bootcamp attendance is required. Up to 10 individuals will be given travel grants of $1,000 each.
Eligibility
Medical house staff, PhDs, advanced medical students, and experienced healthcare workers at CHoRUS sites who are passionate about using AI to improve medical care are eligible. Per NIH guidelines, individuals from disadvantaged backgrounds are encouraged to apply.
Application Process
To be considered, applicants must submit here (1) an updated CV and (2) a personal statement (500 words, maximum) that describes the applicant’s
- professional goals,
- potential contribution to diversity in medical AI,
- potential benefit from attending the AI in Clinical Care bootcamp,
- financial need, and
- other sources of funding available if the applicant does not receive a travel grant.
The AI in Clinical Care Bootcamp
The bootcamp is aimed at beginners to AI and machine learning, so no prior programming experience is required.
The bootcamp will be taught by faculty from CHoRUS sites and the University of Florida College of Medicine.
Before the workshop (self-paced prerequisite instruction available upon registration)
- Introduction to Python (syntax, variables, libraries, loops, conditionals, functions)
- Introduction to Version Control: Reproducibility with Git and GitHub
- FAIR Data for AI (Findable, Accessible, Interoperable, Reusable)
During the workshop
- Hands-on guided programming
- Review of Python fundamentals
- Data Analysis, Processing, and Visualization
- Machine Learning with Structured Electronic Health Record Data
- Special topics seminars with illustrated examples
- Artificial Intelligence in Radiology
- Digital Pathology and AI
- Natural Language Processing (NLP) in Medicine
- Social reception with medical AI researchers
Learning Objectives
By the end of this workshop, bootcamp participants will be able to:
- Navigate the Jupyter Lab environment and create Jupyter notebooks
- Explain the rules that govern Python variables, loops, conditionals, and functions
- Develop and execute Python code for manipulating medical data
- Identify the important Python libraries for biomedical data science
- Explain the advantages of FAIR data and version control for AI collaboration
- Train a machine learning model to predict patient outcomes with structured medical datasets
- Describe the deep learning methods used for radiology, pathology, and text data
- Identify the challenges and opportunities for AI in medical imaging and NLP
- Discuss the importance of multidisciplinary collaboration for advancing medical AI
The NIH Bridge2AI CHoRUS Program
This is a unique opportunity to be a part the Skills and Workforce Development Module of the NIH-funded CHoRUS program, a multicenter, $130 million project intended to build an ecosystem where the benefits of medical AI can reach critical care patients in more geographical areas and of all socioeconomic backgrounds.