Evidence map›Paper›PMID 33176716›Full record

ArticleBMC infectious diseases2020

Malaria Screener: a smartphone application for automated malaria screening.

Hang Yu, Feng Yang, Sivaramakrishnan Rajaraman, Ilker Ersoy, Golnaz Moallem, Mahdieh Poostchi, Kannappan Palaniappan, Sameer Antani, Richard J Maude, Stefan Jaeger

Open access · goldAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
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

27 citing papers in PubMed, 62 citations in OpenAlex.

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  15. Automatic patient-level recognition of fourMicrobiology spectrum · 2024
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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

10 authors at 4 institutions in 3 countries.

Hang YuLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Feng YangLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Sivaramakrishnan RajaramanLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Ilker ErsoyInstitute for Data Science and Informatics, University of Missouri-Columbia, Columbia, MO, 65211, USA.
Golnaz MoallemLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Mahdieh PoostchiLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Kannappan PalaniappanElectrical Engineering and Computer Science Department, University of Missouri-Columbia, Columbia, MO, 65211, USA.
Sameer AntaniLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
Richard J MaudeMahidol Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, 10400, Thailand.
Stefan JaegerLister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA. stefan.jaeger@nih.gov.ORCID http://orcid.org/0000-0001-6877-4318
National Institutes of Health · USUniversity of Missouri · USHarvard University · USTexas Tech University · US

Funding

Quantitative analysis of estrogen and sleep deprivation-induced blood and lymphatic vascular remodeling in the brain systemR01NS110915 · NINDS · UNIVERSITY OF MISSOURI-COLUMBIA · PI GLINSKII, OLGA V, PALANIAPPAN, KANNAPPAN · 2019 to 2023
$2.7M
NINDS NIH HHS R01 NS110915
6 · The paper itself

Abstract

backgroundLight microscopy is often used for malaria diagnosis in the field. However, it is time-consuming and quality of the results depends heavily on the skill of microscopists. Automating malaria light microscopy is a promising solution, but it still remains a challenge and an active area of research. Current tools are often expensive and involve sophisticated hardware components, which makes it hard to deploy them in resource-limited areas.

resultsWe designed an Android mobile application called Malaria Screener, which makes smartphones an affordable yet effective solution for automated malaria light microscopy. The mobile app utilizes high-resolution cameras and computing power of modern smartphones to screen both thin and thick blood smear images for P. falciparum parasites. Malaria Screener combines image acquisition, smear image analysis, and result visualization in its slide screening process, and is equipped with a database to provide easy access to the acquired data.

conclusionMalaria Screener makes the screening process faster, more consistent, and less dependent on human expertise. The app is modular, allowing other research groups to integrate their methods and models for image processing and machine learning, while acquiring and analyzing their data.

Indexed as

SmartphoneData AccuracyHumansImage Processing, Computer-AssistedMachine LearningMalaria, FalciparumMass ScreeningMicroscopyPlasmodium falciparumSensitivity and SpecificitySoftwareAutomated light microscopyConvolutional neural networkMachine learningMalariaSmartphone application

Identifiers

PMID33176716
PMCPMC7656677
OpenAlexW3102000527

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.