Evidence map›Paper›PMID 42645802›Full record

ArticleInfectious disease reports2026

Deep Learning-Based Malaria Parasite Image Classification on Real Microscopy Data.

Francesco Branda, Lilia Andriani, Riccardo Lucis, Annamaria Defilippo, Ugo Lomoio, Barbara Puccio, Giancarlo Ceccarelli, Massimo Ciccozzi, Fabio Scarpa, Pierangelo Veltri and 1 more

Abstract read
In one paragraph

Article in Infectious disease reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Francesco BrandaUnit of Medical Statistics and Molecular Epidemiology, Università Campus Bio-Medico di Roma, Via Àlvaro del Portillo 21, 00128 Rome, Italy.ORCID 0000-0002-9485-3877
Lilia AndrianiUnit of General Clinical Laboratory with Specialized Areas General Clinical Pathology and Substances of Abuse, Microbiology and Virology, Department of Clinical Services, Azienda Socio Sanitaria Territoriale della Valtellina e Alto Lario (ASST Valtellina e Alto Lario), Chiavenna Hospital, Via Cereria 4, 23022 Chiavenna, Italy.ORCID 0000-0002-6671-5741
Riccardo LucisDepartment of Medicine (DMED), University of Udine, Piazzale Kolbe 4, 33100 Udine, Italy.ORCID 0009-0007-3730-3936
Annamaria DefilippoDepartment of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0009-0004-0421-7650
Ugo LomoioDepartment of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0000-0001-8150-0039
Barbara PuccioDepartment of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0009-0002-1189-3628
Giancarlo CeccarelliDepartment of Public Health and Infectious Diseases, University of Rome Sapienza, 00185 Rome, Italy.ORCID 0000-0001-5921-3180
Massimo CiccozziUnit of Medical Statistics and Molecular Epidemiology, Università Campus Bio-Medico di Roma, Via Àlvaro del Portillo 21, 00128 Rome, Italy.ORCID 0000-0003-3866-9239
Fabio ScarpaDepartment of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy.ORCID 0000-0002-3501-714X
Pierangelo VeltriDepartment of Computer Engineering, Modeling, Electronics and Systems (DIMES), University of Calabria, via P. Bucci, 87036 Rende, Italy.ORCID 0000-0003-2494-0294
Pietro Hiram GuzziDepartment of Surgical and Medical Sciences, Magna Graecia University of Catanzaro, Viale Europa, 88100 Catanzaro, Italy.ORCID 0000-0001-5542-2997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

computational pathologydeep learningexplainable artificial intelligence (XAI)malaria diagnosisResNet50Vision Transformer (ViT)

Identifiers

PMID42645802
PMCPMC13512370

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.