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Radiological and morphological features of vanishing lung syndrome development in patients with COVID-19 community-acquired viral pneumonia

2024· article· en· W4393235569 on OpenAlexaboutno aff
О.К. Yakovenko, М.І. Lynnyk, І. В. Ліскіна, V. І. Іgnatieva, Г. Л. Гуменюк, М.G. Palivoda

Bibliographic record

VenueInfusion & Chemotherapy · 2024
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PneumoniaViral pneumoniaRadiological weaponMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Lung2019-20 coronavirus outbreakVirologyPathologyInternal medicineRadiologyOutbreakDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND. Presently actively new direction develops in digital treatment of CТ images – radiomics, that presents the result of co-operation on verge of different sciences (radiology, computer sciences and mathematical statistics). Inaccessible for the unarmed eye additional information of CT images can be got by means of their mathematical treatment and creation of the segmented histograms. Last it is possible to compare and analyse both isolated and with regard to the dynamics of physiopathology descriptions of organs and fabrics at the different human diseases. OBJECTIVE. To define the roentgenologic and morphological features of development of vanishing lung syndrome for patients with non-hospital viral pneumonia. MATERIALS AND METHODS. Data of CТ are analysed in a dynamics for patients with non-hospital viral pneumonia of COVID-19, that were on treatment in SI “National institute of phthisiology and pulmonology named after F.G. Yanovsky of the NAMS of Ukraine” or were directed from other medical establishments. The Dragonfly program from Object Research Systems (Montreal, Canada), which performs micro-X-ray structural analysis of the examined tissues, was used to analyze CT images of chest. Pathomorphological examination was performed in the laboratory of pathomorphology of the institute. RESULTS. Monitoring of CT is conducted in the group, that consisted of 90 patients with non-hospital viral pneumonia of COVID-19. 27 (30,0 %) patients (18 men and 9 women in age from 23 to 68) are educed with the roentgenologic signs of vanishing lung syndrome. 12 from them (9 men and 3 women in age from 23 to 56) were on treatment in the institute in an acute period of disease. Other 15 patients (9 men and 6 women in age from 26 to 68) directed from other curative establishments, where they treated oneself 3-4 months ago. CONCLUSIONS. Micro-X-ray structural analysis of data of CT allows to educe the features of changes of parenchima at development of vanishing lung syndrome. These changes are confirmed by the educed changes at pathomorphological research of postoperative preparations of lungs.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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