Oct. 10, 2022, 1:11 a.m. | Satrajit Chakrabarty, Syed Amaan Abidi, Mina Mousa, Mahati Mokkarala, Isabelle Hren, Divya Yadav, Matthew Kelsey, Pamela LaMontagne, John Wood, Michae

cs.LG updates on arXiv.org arxiv.org

Efforts to utilize growing volumes of clinical imaging data to generate tumor
evaluations continue to require significant manual data wrangling owing to the
data heterogeneity. Here, we propose an artificial intelligence-based solution
for the aggregation and processing of multisequence neuro-oncology MRI data to
extract quantitative tumor measurements. Our end-to-end framework i) classifies
MRI sequences using an ensemble classifier, ii) preprocesses the data in a
reproducible manner, iii) delineates tumor tissue subtypes using convolutional
neural networks, and iv) extracts diverse radiomic …

arxiv automation cancer imaging neuro oncology research workflow workflow automation

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Intern - Robotics Industrial Engineer Summer 2024

@ Vitesco Technologies | Seguin, US