Optical Systems for <i>in Vivo</i> Molecular Imaging of Cancer
Bibliographic record
Abstract
Progress toward a molecular characterization of cancer would have important clinical benefits; thus, there is an important need to image the molecular features of cancer in vivo. In this paper, we describe a comprehensive strategy to develop inexpensive, rugged and portable optical imaging systems for molecular imaging of cancer, which couples the development of optically active contrast agents with advances in functional genomics of cancer. We describe initial results obtained using optically active contrast agents to image the expression of three well known molecular signatures of neoplasia: including over expression of the epidermal growth factor receptor (EGFR), matrix metallo-proteases (MMPs), and oncoproteins associated with human papillomavirus (HPV) infection. At the same time, we are developing inexpensive, portable optical systems to image the morphologic and molecular signatures of neoplasia noninvasively in real time. These real-time, portable, inexpensive systems can provide tools to characterize the molecular features of cancer in vivo.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".