📊 [CHI 2023] UTA11: Findings dataset.

📊 [CHI 2023] UTA11: a medical imaging dataset of patients with DICOM files provided by radiologists.

Project website.

The webpage of the MIMBCD-UI research work.

📊 [CHI 2023] UTA11: Rates (BIRADS) dataset.

[IJHCS] UTA7: a dataset of rates (BI-RADS) provided by clinicians resulted from classifying the given medical images for breast cancer diagnosis.

[AVI 2020] UTA4: Rates (BIRADS) dataset.

[IJHCS] UTA7: a clinical dataset with medical imaging and patient co-variables.

[IJHCS] UTA7: a dataset with DICOM files of medical imaging provided by radiologists. The work was published in the International Journal of Human-Computer Studies.

Official source code for Health Tech , a health care service provider which uses artifical intelligence to tackle the problems .

Website repository for modelhub.ai

Create a medical imaging application based on different DL models.

[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.

[IJHCS] UTA7: a dataset of clinicians' results of the System Usability Scale (SUS) answers from our user studies.

[IJHCS] UTA7: a dataset of clinicians' NASA-TLX results from our user studies.

[IJHCS] UTA7: a dataset of heatmaps and images resulted from computing the given abnormalities which were manually delineated by clinicians while annotating the breast cancer lesions.

[IJHCS] UTA7: a dataset of clinicians' demographic results from our user studies.

[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.

[IJHCS] UTA7: a dataset with assistant information such as messages and outputs.

[IJHCS] UTA7: a dataset from the results of the affinity diagrams extracted from our focus groups.