🌐 MIDA Project Webpage
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Updated
Dec 7, 2018 - CSS
Medical imaging is the technique and process of creating visual representations of the interior of a body for clinical analysis, and medical intervention.
🌐 MIDA Project Webpage
[IJHCS] UTA7: a dataset of clinicians' NASA-TLX results from our user studies.
[IJHCS] UTA7: a dataset with assistant information such as messages and outputs.
Website pages for Model Deployment of ICH Detection using DL
[AVI 2020] UTA4: Severity (BIRADS) & Pathology Classifications dataset. The work was presented in the Advanced Visual Interfaces conference.
📊 [CHI 2023] UTA11: Rates (BIRADS) dataset.
Website for the Imperial First Year Topics Project.
[IJHCS] UTA7: a dataset of time-on-task during our user studies extracted from clinicians while interacting with our assistant across the breast cancer diagnosis.
Project website.
[IJHCS] UTA7: a dataset of clinicians' demographic results from our user studies.
[IJHCS] UTA7: a clinical dataset with medical imaging and patient co-variables.
[IJHCS] UTA7: a dataset of manual annotations provided by radiologists in medical imaging for breast cancer diagnosis. The work was published in the International Journal of Human-Computer Studies.
The webpage of the MIMBCD-UI research work.
Deployment Files for MedicAI Application Server Deployed on Flask using Heroku.
[IJHCS] UTA7: a dataset from the results of the affinity diagrams extracted from our focus groups.
📊 [CHI 2023] UTA11: Findings dataset.
Create a medical imaging application based on different DL models.
[IJHCS] UTA7: a dataset of rates (BI-RADS) provided by clinicians resulted from classifying the given medical images for breast cancer diagnosis.