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Record W2602359960 · doi:10.1080/14737159.2017.1310619

Portable devices and mobile instruments for infectious diseases point-of-care testing

2017· review· en· W2602359960 on OpenAlex
Luc Bissonnette, Michel G. Bergeron

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExpert Review of Molecular Diagnostics · 2017
Typereview
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSoftware portabilityPoint-of-care testingPoint of careTurnaround timeComputer scienceMobile deviceHealth careRisk analysis (engineering)MedicineData scienceWorld Wide WebPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Rapidity, simplicity, and portability are highly desirable characteristics of tests and devices designed for performing diagnostics at the point of care (POC), either near patients managed in healthcare facilities or to offer bioanalytical alternatives in external settings. By reducing the turnaround time of the diagnostic cycle, POC diagnostics can reduce the dissemination, morbidity, and mortality of infectious diseases and provide tools to control the global threat of antimicrobial resistance. Areas covered: A literature search of PubMed and Google Scholar, and extensive mining of specialized publications, Internet resources, and manufacturers' websites have been used to organize and write this overview of the challenges and requirements associated with the development of portable sample-to-answer diagnostics, and showcase relevant examples of handheld devices, portable instruments, and less mobile systems which may or could be operated at POC. Expert commentary: Rapid (<1 h) diagnostics can contribute to control infectious diseases and antimicrobial resistant pathogens. Portable devices or instruments enabling sample-to-answer bioanalysis can provide rapid, robust, and reproducible testing at the POC or close from it. Beyond testing, to realize some promises of personalized/precision medicine, it will be critical to connect instruments to healthcare data management systems, to efficiently link decentralized testing results to the electronic medical record of patients.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.330
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it