content — AIM

AI and Imaging can predict Immunotherapy response

We used AI to quantify the radiographic phenotype of a tumor to predict IO response.

publicationai medicineMarch 1, 20192019hugo-aerts, ai, stefano-trebeschi, oncology

Our publication about artificial intelligence in cancer imaging was highlighted on the cover of CA: A Cancer Journal for clinicians.

newsai medicineFebruary 28, 20192019ahmed-hosny, hugo-aerts, raymond-mak, ai, radiation-oncology

Trial Design for the evaluation of oncology devices

JNCI published our study about trial design of novel technologies for cancer treatment, including artificial intelligence algorithms.

publicationai medicineFebruary 28, 20192019ai, raymond-mak, danielle-bitterman

Artificial Intelligence in Cancer Imaging

A review of AI applications in the imaging of several tumor types has been published in CA: A Cancer Journal for clinicians.

publicationai medicineFebruary 27, 20192019ahmed-hosny, hugo-aerts, raymond-mak, ai, radiation-oncology, udo-hoffmann

Deep Learning for Identification of Extranodal Extension

Deep learning identifies extranodal extension in head and neck cancer better than radiologists; potential to be used for treatment decisions.

publicationai medicineFebruary 13, 20192019benjamin-kann, oncology

Publication highlighted in Nature Grand Challenges

AIM’s publication “AI in Radiology” was featured in the Nature about promising technologies transforming the world.

newsai medicineSeptember 1, 20182019ahmed-hosny, hugo-aerts, ai

Cover feature in Nature Reviews Cancer

Our publication “Artificial Intelligence in Radiology” was highlighted on the cover of Nature Reviews Cancer.

newsai medicineAugust 3, 20182018ahmed-hosny, hugo-aerts, ai

Artificial Intelligence in Radiology

Nature Reviews Cancer published our opinion article on the application of artificial intelligence to image-based tasks in the field of radiology.

publicationai medicineAugust 2, 20182018ahmed-hosny, hugo-aerts, ai

Deep Learning for Lung Cancer Prognostication

PLOS Medicine published our study exploring deep learning for predicting overall survival in lung cancer patients.

AIM article awarded by IMIA as one of the best

Our article about radiomics-genomic interactions in lung cancer was selected by IMIA as one of the best articles of the year.

newsai medicineJuly 1, 20182018hugo-aerts, ai

Data Analysis Strategies in Medical Imaging

Clinical Cancer Research published our article outlining best practices for analyzing medical imaging data using AI.

publicationai medicineJanuary 14, 20182018ahmed-hosny, hugo-aerts, ai

Cancer Research published our computational AI system

We published about our computational system to quantify tumor characteristics on medical imaging.

publicationai medicineNovember 1, 20172017hugo-aerts, ai, joost-van-griethuysen

Defining the Biological Basis of Radiomic Phenotypes

eLife published our study revealing links between radiomic, genomic, and clinical data of lung cancer patients.

publicationai medicineMay 12, 20172017hugo-aerts, ai

Decoding Tumour Phenotype in Cancer Imaging

Nature Communications published our study outlining the extraction of radiomic features from cancer imaging data.

publicationai medicineJuly 10, 20142014hugo-aerts, ai, radiation-oncology