Application of PET to the Diagnosis, Staging, and Treatment of Locally Advanced Non-small Cell Lung Cancer
Bibliographic record
Abstract
The strength of positron emission tomography (PET) lies in the application of its underlying technological and molecular biology advancements to clinical practice and pharmacological development. Currently, PET is used to identify malignant pulmonary nodules, evaluate mediastinal disease, detect distant metastasis, assess response to therapy, and identify novel oncologic drug targets. Over the last decade, PET has also increasingly influenced the management of locally advanced nonsmall cell lung cancer (NSCLC) by directing chemoradiation and surgical treatment. Although the majority of clinical trials and practice have used 2-18F- fluoro-2-deoxy-D-glucose (FDG) as the radiopharmaceutical agent for evaluating NSCLC, novel radiolabeled tracers, radiopharmaceutical agents, and targeted immunotherapy drugs are actively being investigated to improve the treatment of NSCLC. This review focuses on the utility of PET for diagnosing malignant pulmonary nodules, staging the extent of disease, and evaluating immuno-oncology therapies in locally advanced NSCLC. Keywords: Drug development, immunotherapy, molecular genetics, NSCLC, PET, staging.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".