This unique and immersive traineeship is designed to equip you with practical skills and knowledge through hands-on, project-based experiences in applying advanced AI tools to address specific questions in basic, translational, or clinical research and healthcare delivery. Bring your own projects or inquiries and learn how to harness AI-driven data analysis, causal inference techniques, and wearable technology applications in the field of movement disorders. Our primary goal is to help you develop high-level familiarity and a deep understanding of AI-based productivity tools in the clinical management and research of movement disorders. Throughout the program, you’ll gain practical skills that can be directly applied to your work. Participants can expect continuous support from the program in publishing their project results beyond the traineeship.
Dr. Bin Hu is an endowed professor and founding director of Translational Neuroscience Division at the Cumming School of Medicine, University of Calgary. He is also affiliated with the Hotchkiss Brain Institute and the Alberta Children’s Hospital Research Institute. Dr. Hu's research focuses on movement disorders, particularly Parkinson’s Disease (PD), and he is renowned for pioneering innovations in digital health and wearable technologies to enhance treatment and telehealth solutions for neurological disorders.
He is the driving force behind large-scale international projects like the Ambulosono-ACSCON-OpenDH, which aims to develop second-generation wearable systems and digital health platforms. His work also explores non-pharmaceutical interventions, using advanced technological tools to address motor and cognitive decline in neurodegenerative diseases. One notable area of his research is the study of music-induced paradoxical movement in Parkinson's disease, as well as the development of evidence-based digital health interventions
AI and Data Science for Movement Disorders:
This area focuses on applying Large Language Models (LLMs) and data science techniques to ensure high-quality data collection, processing, and analysis. Emphasis will be placed on maintaining data integrity, enhancing precision, and automating workflows in movement disorder research. This would include applications to patient diaries and wearable movement tracking devices.
Causal Inference Analysis:
Learn how to apply causal inference methods and AI tools to identify cause-and-effect relationships from observational clinical data. This area emphasizes understanding the underlying mechanisms of movement disorders and developing non-pharmaceutical interventions for rehabilitation.
Large Language Models (LLMs) and Synthetic Data:
Explore the use of LLMs and synthetic data generation to enhance analysis of high-dimensional data from sources like patient diaries, wearable devices, and rehabilitation training. Techniques will include integrating various data streams to study patient behavior, symptom patterns, and the effects of movement interventions on quality of life.
Wearable Technology and Music-Based Rehabilitation:
Participants will learn about Dr. Hu’s Ambulosono program, which uses wearable technology and music-based reinforced walking exercises to monitor and improve patients' daily activity. The focus will be on how to analyze the data collected from patients’ movements and activities to develop actionable insights for therapy.
Data Integrity and Precision in Movement Tracking:
Techniques for ensuring data quality in patient tracking devices and how to automate data analysis to identify patterns in movement disorders.
Causal Inference in Clinical Data:
Apply statistical and machine learning methods to infer causal relationships between variables in clinical observational studies. You will learn to draw meaningful conclusions that can lead to targeted interventions.
Using LLMs and Synthetic Data for Analysis:
Techniques to integrate LLMs and synthetic data generation in analyzing large datasets, including movement tracking and patient diaries. This will enhance decision-making processes and personalize treatment approaches.
Wearable Technology in Rehabilitation:
Hands-on training in using wearable devices to track patient movements, along with analyzing the data to optimize rehabilitation programs. Learn how to measure and improve patient adherence to exercise interventions using music-based feedback.
By the end of the traineeship, participants will be able to:
Analyze and Implement Data Science Techniques:
Apply Causal Inference Methods:
Utilize LLMs and Synthetic Data:
Develop and Apply Wearable Technologies:
MODULES
Module 1: AI and Data Science in Movement Disorders
Topics Covered:
Learning Outcomes:
Module 2: Causal Inference Analysis in Clinical Data
Topics Covered:
Learning Outcomes:
Module 3: Integrating LLMs and Synthetic Data for Analysis
Topics Covered:
Learning Outcomes:
Module 4: Wearable Technology and Music-Based Rehabilitation
Topics Covered:
Learning Outcomes:
SCHEDULE
Week 1:
Week 2:
Week 3:
Week 4:
Total Number of Modules | 4 |
Time duration of Each module | 60 minutes |
Total Program Cost | $350 |
This program allows Merit Applications. This program allows merit-based applications for virtual and onsite clinical and research programs. If you are successfully awarded under this category, Trialect or the host mentor will cover the tuition fee only. All applications will be evaluated based on merit. Due to the high level of competition, the chances of being selected under the merit category are quite limited.
All
Host Name: Bin Hu MD. PhD, Founder of Division of Translational Medicine
Affiliation: Translational Neuroscience, Cumming School of Medicine, University of Calgary
Address: 3330 Hospital Dr NW, Calgary, AB T2N 4Z5, Canada
Website URL: https://cumming.ucalgary.ca/
Disclaimer:It is mandatory that all applicants carry workplace liability insurance, e.g., https://www.protrip-world-liability.com (Erasmus students use this package and typically costs around 5 € per month - please check) in addition to health insurance when you join any of the onsite Trialect partnered fellowships.
Nov 1st, 2024
Duration | Fee |
---|---|
2 weeks | $625.00 |
6 weeks | $1,500.00 |
12 weeks | $2,750.00 |
This program allows Merit Applications. This program allows merit-based applications for virtual and onsite clinical and research programs. If you are successfully awarded under this category, Trialect or the host mentor will cover the tuition fee only. All applications will be evaluated based on merit. Due to the high level of competition, the chances of being selected under the merit category are quite limited.
All
Host Name: Bin Hu MD. PhD, Founder of Division of Translational Medicine
Affiliation: Translational Neuroscience, Cumming School of Medicine, University of Calgary
Address: 3330 Hospital Dr NW, Calgary, AB T2N 4Z5, Canada
Website URL: https://cumming.ucalgary.ca/
Disclaimer:It is mandatory that all applicants carry workplace liability insurance, e.g., https://www.protrip-world-liability.com (Erasmus students use this package and typically costs around 5 € per month - please check) in addition to health insurance when you join any of the onsite Trialect partnered fellowships.
Commonly asked questions about this program from the host and other attendees.