Executive function after childhood cancer: Insights from network neuroscience
Bibliographic record
Abstract
In this review, we examine the empirical literature on the cognitive late effects of childhood acute lymphoblastic leukemia (ALL) and brain tumors, with a focus on executive function and its neural underpinnings. Executive function is a critical domain, influencing survivors' educational attainment, social relationships, and overall quality of life. We first examine behavioral evidence of executive function impairments observed after cancer diagnosis and treatment. We then explore neuroscientific insights, integrating findings from volumetric analyses, functional imaging, and network-based approaches to uncover neural mechanisms underlying these deficits. Special emphasis is placed on the value of network-based methods, including structural and functional connectivity as well as overall network organization. Finally, we identify promising directions for future research aimed at deepening our understanding of these cognitive late effects and developing effective strategies to mitigate them. This review seeks to bridge behavioral and neural perspectives, offering insights that can inform clinical practices and improve outcomes for childhood cancer survivors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".