qradiomics workflow overview

Introducing qradiomics — A Unified Radiomics CLI for Reproducible Research

We are releasing qradiomics — an open-source Python CLI that unifies more than a decade of Choi Lab radiomics work into a single, reproducible, pip-installable toolkit. What is qradiomics? qradiomics (command: qr) is a radiomics research CLI built for the full data flow from raw DICOM to published-grade results: DICOM download → conversion → feature extraction → clinical merge → modeling Each step is a single Unix-style command. Pipelines are assembled from those atomic commands using plain JSON plans, executed by Nextflow (per-patient parallel), Prefect, or inline. One command gets you started: ...

May 20, 2026 · 5 min · 900 words · Wookjin Choi

Artificial Intelligence in Radiation Oncology

October 15, 2021 · 0 min · 0 words · Wookjin Choi

PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma

Jung Hun Oh, Wookjin Choi, Euiseong Ko, Mingon Kang, Allen Tannenbaum, Joseph O Deasy The authors wish it to be known that, in their opinion, Jung Hun Oh and Wookjin Choi should be regarded as Joint First Authors. https://academic.oup.com/bioinformatics/article/37/Supplement_1/i443/6319702 https://github.com/mskspi/PathCNN/raw/main/img/pathcnn.png An illustration of biological interpretation. (A) Grad-CAM procedure to generate class activation maps. The two images on the left bottom represent an example of the class activation maps for a sample in the cohort, which were generated from Grad-CAM procedure; (B) statistical analysis to identify significantly different pathways between the LTS and non-LTS groups. LTS, long-term survival; CNN, convolutional neural network; ReLU, rectified linear unit ...

July 22, 2021 · 2 min · 286 words · Wookjin Choi