Diagnostic and follow-up MRIs, CTs, Radiotherapy and Radiomics data of Brain Metastases
Bibliographic record
Abstract
Summary: This repository presents a comprehensive longitudinal dataset comprising of 185 imaging studies (magnetic resonance imaging and computed tomography scans) from 40 patients diagnosed with metastatic brain cancer, with the dataset featuring detailed segmentations of 65 brain metastases, along with pre-treatment radiotherapy dosage distribution maps (RT plan). The dataset includes manual segmentations that encompass three distinct regions in the brain: the enhancing tumor region, the edema and the necrotic core, thus, providing a comprehensive representation of tumor morphology for advanced analysis. The data available in this repository aims to support research and evaluation of automatic brain metastases detection, lesion segmentation, disease assessment, treatment planning, and the development of pertinent predictive and prognostic tools. Acknowledgements: This study was financially supported by the Cyprus Cancer Research Institute through the PROTEAS project (Call: Bridges in Research Excellence CCRI_2020_FUN_001; Grant ID: CCRI_2021_FA_LE_105) and has been approved by the Cyprus National Bioethics Committee (ID: EEBK/ΕΠ/2021/72).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".