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Validating the ability to detect Amyotrophic Lateral Sclerosis (ALS) through
Search Engine Interactions
In Collaboration with
We are looking for participants between 18 and 100 years of age
We have developed a model to predict Amyotrophic Lateral Sclerosis (ALS) from people’s interactions with search engines. Our model is based on labels deduced from the queries made by people who stated (in their queries) that they have ALS. The goal of this study is to validate this model using data from clinically verified cases and publish an academic paper showing the accuracy of the model. The data collected through this study, because it is clinically verified, will allow such determination.
People who chose to participate will be referred to the experiment website. On the website they will consent to participate, provide their age and gender and the date of their diagnosis. Users 18 years of age or more can participate in the experiment.
Then, users will receive a random code and will be asked to enter this code on Bing as a query. This query will be used to link an anonymous participant to their queries on Bing. The length of participation for each user is estimated at 10 minutes. Subjects may request the removal of their data from the analysis by sending the principal investigator the random code.
Users in this population are referred to as the condition cohort. Data of the control cohort be classified by our ALS prediction model, and the outcome measures will be computed.