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“Hacking” with Social Media

8 minute read

Published:

As part of a panel discussion on ‘Social Media and its Impact on Data Privacy for Corporates and Employees’ held during the World Economic Forum in Davos, Jan 2018, I was asked to provide some insights into how one might obtain compromising private information from social media.

projects

publications

Automated Knee X-ray Report Generation

Published in NeurIPS ML4H, 2017

Knee X-ray exams consisting of sets of images and corresponding radiological reports can be used as part of a learning framework to determine image-text correspondence and hence automate the generation of such reports for new X-ray exams.

Recommended citation: Gasimova, A., Montana, G., Rueckert, D. (2017). "Automated Knee X-ray Report Generation." NeurIPS ML4H.

Automated Enriched Medical Concept Generation for Chest X-ray Images.

Published in MICCAI ML-CDS, 2019

Given a small amount of manual annotations, clinically and visually-important concepts can be learned from raw textual radiology reports and consequently used at image annotations in automated report generation.

Recommended citation: Gasimova, A., 2019. "Automated enriched medical concept generation for chest X-ray images." In Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support (pp. 83-92). Springer, Cham.

Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation

Published in MICCAI, 2020

Semantic-preserving latent space for minor as well as extremely undersampled MR images capable of achieving promising results on a diagnostic report generation task.

Recommended citation: Gasimova, A., Seegoolam, G., Chen, L., Bentley, P. and Rueckert, D., 2020, October. "Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation." In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 333-342). Springer, Cham.

Machine learning model for predicting lung cancer recurrence after surgical treatment: A retrospective study using NLST and European hospital data

Published in ESMO Abstracts, 2023

ML model outperforms clinical staging prediction of lung cancer recurrence in preoperative settings.

Recommended citation: Valter A., Kordemets T., Gasimova A., Waterfield Price N., Freitag L., Vanakesa T., Almre I., Oselin K. (2023). "Machine learning model for predicting lung cancer recurrence after surgical treatment: A retrospective study using NLST and European hospital data." ESMO.

Imaging AI prognosis of early stage lung cancer using CT radiomics.

Published in ESMO Abstracts, 2024

The ML survival model outperforms clinical staging in patient risk-stratification and time-dependent lung cancer recurrence prediction.

Recommended citation: Valter A., Kordemets T., Gasimova A., Heames B., Waterfield Price N., Hodgkinson G., Vanakesa T., Almre I., Freitag L., Carbone D., Oselin K. (2024). "Imaging AI prognosis of early stage lung cancer using CT radiomics." ESMO.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.