Current Analytical Methods and Challenges for the Clinical Diagnosis of Invasive Pulmonary Aspergillosis Infection
Bibliographic record
Abstract
In the last decade, pulmonary fungal infections such as invasive pulmonary aspergillosis (IPA) have increased in incidence due to the increased number of immunocompromised individuals. This increase is especially problematic when considering mortality rates associated with IPA are upwards of 70%. This high mortality rate is due to, in part, the length of time it takes to diagnose a patient with IPA. When diagnosed early, mortality rates of IPA decrease by as much as 30%. In this review, we discuss current technologies employed in both medical and research laboratories to diagnose IPA, including culture, imaging, polymerase chain reaction, peptide nucleic acid-fluorescence in situ hybridization, enzyme-linked immunosorbent assay, lateral flow assay, and liquid chromatography mass spectrometry. For each technique, we discuss both promising results and potential areas for improvement that would lead to decreased diagnosis time for patients suspected of contracting IPA. Further study into methods that offer increased speed and both analytical and clinical sensitivity to decrease diagnosis time for IPA is warranted.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".