Prof Sergey Avdeev, MD, PhD is an expert in Pulmonology at Sechenov University (Russia). As of October 2026, ScienceLeadR ranks Sergey Avdeev in the top 1% of experts worldwide for Coronavirus Infections, Pneumonia and COVID-19. Sergey Avdeev has authored 496 publications, the most recent in 2026, and is an investigator in 10 clinical trials. SLR score: 1,704 (community average: 125). How the SLR is computed.

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Prof Sergey Avdeev, MD, PhD Sechenov University Russia
1 704 ScienceLeadR Reputation 1704
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Pulmonology

Subspecialties: Biochemistry - Infectiology - Cardiology

Full career – Last 3 years

Main Topics

Publications and Clinical Studies

Publications – Clinical Studies

Profile data updated on

Organizations

Career arc: 2017 - 2026

Source: PubMed

Sechenov University

Publications Synthesis

Sources: PubMed, OpenAlex

Breakdown by type

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Latest Publications

5 most recent indexed articles

Source: Pubmed

Title Journal Year Citations
Shared Enrichment of the MUC5B Variant rs35705950 in Idiopathic Pulmonary Fibrosis and Fibrotic Hypersensitivity Pneumonitis: Evidence from a Russian Cohort.
PMID 42938222 — idiopathic pulmonary fibrosis, gene frequency, fibrosis, hypersensitivity, pulmonary fibrosis, alveolitis, extrinsic allergic, alleles, genotype, lung diseases, interstitial
Diagnostics (Basel)20260
Exhaled Breath Analysis for Detection of Interstitial Lung Diseases Using Real-Time PTR-TOF-MS.
PMID 42883718 — lung, respiration, volatile organic compounds, classification, biomarkers, machine learning, lung diseases, lung diseases, interstitial
Int J Mol Sci20260
Exhaled breath volatile organic compounds in cystic fibrosis: a systematic review.
PMID 42617629 — fibrosis, respiration, volatile organic compounds, biomarkers, cystic fibrosis, metabolomics, infections
J Breath Res20260
[Advanced diagnostic capabilities for cough assessment utilizing the neural network model «CoughScan»: findings from a prospective, comparative observational study].
PMID 42625540 — therapeutics, cough, neural networks, computer
Ter Arkh20260
Rapid Classification and Deep Learning-Based Development Estimation of the Seeds of Helianthus annuus.
PMID 42452139 — classification, seeds, deep learning, lighting, learning
Plants (Basel)20260

Clinical Studies 10

Sources: ClinicalTrials, EU CTIS

Synthesis

Principal Investigator: 2

By phase:

N/A 6
Phase 3 2
Phase 2 1
Phase 4 1

By status:

Completed 9
Unknown 1

By type:

Interventional 7
Observational 3

By Monocentric/Multicentric:

monocentric 5
multicentric2to4 1
multicentric5to9 0
multicentricup10 4

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