Evidence map›Paper›PMID 39598966›Full record

ArticleSensors (Basel, Switzerland)2024

Deep Learning-Based Classification of Macrofungi: Comparative Analysis of Advanced Models for Accurate Fungi Identification.

Sifa Ozsari, Eda Kumru, Fatih Ekinci, Ilgaz Akata, Mehmet Serdar Guzel, Koray Acici, Eray Ozcan, Tunc Asuroglu

Abstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
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  12. Classification of Mycena andSensors (Basel, Switzerland) · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sifa OzsariDepartment of Computer Engineering, Faculty of Engineering, Ankara University, Ankara 06830, Türkiye.ORCID 0000-0002-0531-4645
Eda KumruGraduate School of Natural and Applied Sciences, Ankara University, Ankara 06830, Türkiye.ORCID 0009-0000-7417-6197
Fatih EkinciDepartment of Medical Physics, Institute of Nuclear Sciences, Ankara University, Ankara 06100, Türkiye.ORCID 0000-0002-1011-1105
Ilgaz AkataDepartment of Biology, Faculty of Science, Ankara University, Ankara 06100, Türkiye.
Mehmet Serdar GuzelDepartment of Computer Engineering, Faculty of Engineering, Ankara University, Ankara 06830, Türkiye.ORCID 0000-0002-3408-0083
Koray AciciDepartment of Artificial Intelligence and Data Engineering, Faculty of Engineering, Ankara University, Ankara 06830, Türkiye.ORCID 0000-0002-3821-6419
Eray OzcanDepartment of Computer Engineering, Faculty of Engineering, Ankara University, Ankara 06830, Türkiye.ORCID 0000-0002-5180-9884
Tunc AsurogluFaculty of Medicine and Health Technology, Tampere University, 33720 Tampere, Finland.ORCID 0000-0003-4153-0764

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on the classification of six different macrofungi species using advanced deep learning techniques. Fungi species, such as

Indexed as

Deep LearningFungideep learningDenseNet121fungi identificationmachine learning modelsmacrofungi classification

Identifiers

PMID39598966
PMCPMC11598773

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.