Open sina-mansour opened 4 years ago
(Image: CC-BY license, The Turing Way Community, & Scriberia. Zenodo. http://doi.org/10.5281/zenodo.3332808) :tada: Welcome to the 2020 OHBM Hackathon! :tada: We're really excited to have your input on this repository and welcome your idea! :sparkling_heart: If you haven't done so already, please make sure you check out our Code of Conduct. Did you issue a new hackathon project? Please check if you have provided all relevant information and an image for the website.
This is interesting project. I’d be curious to learn what the comparison would tell us. It may have some connections to neuropredict and confounds libraries I’m working on, which may also serve another baseline in the comparison.
Hi @sina-mansour! Thanks a lot for your project. Unless I am mistaken, In think that your project co-lead (Ye Tian) is not registered yet to the event. Can you please ask them to register or list them as project collaborators if they are not joining the event? Thank you!
hi @ohbm/project-monitors My project is ready!
Hi @sina-mansour! Thanks a lot for your project. Unless I am mistaken, In think that your project co-lead (Ye Tian) is not registered yet to the event. Can you please ask them to register or list them as project collaborators if they are not joining the event? Thank you!
Hi @cmaumet, I'll make sure to ask other project leads to also register for the event.
@DorienHuijser I think we have an image for this project to add to the website. :tada: :wink:
Hi @sina-mansour! Thanks a lot for your project. Unless I am mistaken, In think that your project co-lead (Ye Tian) is not registered yet to the event. Can you please ask them to register or list them as project collaborators if they are not joining the event? Thank you!
Hi @cmaumet, just let you know that I have just registered. Thank you. Ye
@sina-mansour I removed the video link to avoid unexpected events in the video channel. Would you add and pin that information to the mattermost channel, please? Thanks.
@@sina-mansour Thank you very much for your project submission. Your project looks ready. Welcome aboard! :hugs: 🎊
Project info
Title: Prediction of age and intelligence, a basic machine learning model
Project lead: Sina Mansour L. and Ye Tian (@sina-mansour and @yetianmed)
Timezone: Melbourne UTC+10
Hub: Asia and Pacific
Description:
Emerging evidence suggests the outstanding utility of multimodal neuroimaging data in predicting individual variation in age and cognition. However, it is unclear whether the predictive utility of such measures is a global effect or is consistently attributed to certain localized patterns of brain structure and connectivity.
This project aims to evaluate and develop an analysis framework for optimal performance of age and behavior (e.g. fluid intelligence) prediction using measures of brain structure and connectivity. The goal is to achieve both overall high prediction accuracy in cross-validated samples and high consistency in the estimated predictors (e.g. regions/connections) if possible. A secondary aim of the project is to investigate the potential markers of sub-clinical cognitive decline through simultaneous prediction of age and cognition in a healthy adult cohort.
Link to project: 2020_ohbm_brainhack_machine_learning_project
Mattermost handle:
sina_mansour_l
andyetian
Goals for the OHBM Brainhack: Collecting implementations of machine learning models to predict age and cognition. This will be followed by a future evaluation of prediction accuracy and feature selection consistency in prediction models of age and IQ using multimodal neuroimaging dataset.
Good first issues: Step 1: Clone the repository Step 2: Join our chat channel Step 3: Register your team Step 4: Start coding :)
Skills: General knowledge about neuroimaging modalities, neuropsychology, and familiarity with a programming language (Python, Matlab, or any language you prefer :wink: )
Chat channel: mattermost.brainhack.org/brainhack/channels/brainhack-ml
Video channel: Please have a look at the mattermost channel to know the video channel.
Participant capacity: We look forward to maximum participation from the neuroimaging community. There is no limit to the number of participants, we will try our best to provide static information, and build an FAQ system to ensure we can provide feedback to participants.
Contributions: All contributors (participants and teams) will be listed in our public repository. After post hoc evaluations of the models, participants submitting well-performing models will be contacted for future collaboration on potential publications.
Project submission
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