Abstract
Hanlin Jiang, Hui Xi, Mario Juhas
Abstract
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African malaria deaths set to dwarf covid-19 fatalities as pandemic hits control efforts, WHO warns.
2020
Unresolved referenced work
1996
Unresolved referenced work
2021
Automatic detection of Trypanosomosis in thick blood smears using image pre-processing and deep learning
2020
Geographical origin of chronic Chagas disease patients in Brazil impacts the performance of commercial tests for anti-T. cruzi IgG
10.1590/0074-02760210032 · 2021
10.1086/508667
10.1086/508667
10.3390/pathogens10091120
10.3390/pathogens10091120
10.1016/j.pt.2017.04.001
10.1016/j.pt.2017.04.001
10.1371/journal.ppat.1008097
10.1371/journal.ppat.1008097
The life-cycle of Toxoplasma gondii reviewed using animations
10.1186/s13071-020-04445-z · 2020
Macrophage Polarization in Leishmaniasis: broadening horizons
crossref
Confidence 100%
ror
Confidence 99%
pubmed
Confidence 98%
europepmc
Confidence 96%
openalex
Confidence 95%
unpaywall
Confidence 95%
doaj
Confidence 92%
datacite
Confidence 0%
10.3389/fimmu.2018.02529 · 2018
10.1097/00004347-199110000-00016
10.1097/00004347-199110000-00016
Trichomonas vaginalis: pathogenicity and potential role in human reproductive failure
10.1007/s15010-015-0860-0 · 2016
10.1007/978-3-030-63384-4
10.1007/978-3-030-63384-4 · 2021
Mass drug administration can be a valuable addition to the malaria elimination toolbox
2019
Comparison of three diagnostic methods (microscopy, RDT, and PCR) for the detection of malaria parasites in representative samples from Equatorial Guinea
10.1186/s12936-018-2481-4 · 2018
Challenges in laboratory diagnosis of Malaria in a low resource country among cases of acute febrile illness at tertiary care hospital in eastern Nepal: Comparative study on Conventional Vs Molecular approach
2021
Label-free imaging and classification of live P. falciparum enables high performance parasitemia quantification without fixation or staining
10.1371/journal.pcbi.1009257 · 2021
Transfer learning for toxoplasma gondii recognition
2020
Malaria diagnosis: a brief review
10.3347/kjp.2009.47.2.93 · 2009
Applying Faster R-CNN for Object Detection on Malaria Images
2017
Systematic review and meta-analysis of diagnostic accuracy of loop-mediated isothermal amplification (LAMP) methods compared with microscopy, polymerase chain reaction and rapid diagnostic tests for malaria diagnosis
10.1016/j.ijid.2020.07.009 · 2020
Deep learning in medical imaging: general overview
10.3348/kjr.2017.18.4.570 · 2017
Challenges related to artificial intelligence research in medical imaging and the importance of image analysis competitions
2019
10.3390/cancers11111673
10.3390/cancers11111673
Deep neural networks improve radiologists’ performance in breast cancer screening
10.1109/tmi.2019.2945514 · 2019
Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients
2021
10.1016/j.media.2020.101813
10.1016/j.media.2020.101813
Deep Learning for Imaging and Detection of Microorganisms
10.1016/j.tim.2021.01.006 · 2021
Multi-stage malaria parasite recognition by deep learning
10.1093/gigascience/giab040 · 2021
Automated blood smear analysis for mobile malaria diagnosis. Mobile Point-of-Care Monitors and Diagnostic Device
2014
Geometry-aware cell detection with deep learning
10.1128/msystems.00840-19 · 2020
A novel stacked CNN for malarial parasite detection in thin blood smear images
10.1109/access.2020.2994810 · 2020
Parasitologist-level classification of apicomplexan parasites and host cell with deep cycle transfer learning (DCTL)
10.1093/bioinformatics/btaa513 · 2020
Image analysis and machine learning for detecting malaria
10.1016/j.trsl.2017.12.004 · 2018
Leishmaniasis Parasite Segmentation and Classification Using Deep Learning
10.1007/978-3-319-94544-6_6 · 2018
Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning
10.1038/s41377-018-0110-1 · 2018
Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models
10.1186/s12859-021-04036-4 · 2021
10.1007/978-981-15-1286-5_70
10.1007/978-981-15-1286-5_70 · 2020
Convolutional Neural Networks for Chagas’ Parasite Detection in Histopathological Images
2021
A machine learning-based system for detecting leishmaniasis in microscopic images
10.1186/s12879-022-07029-7 · doi-reference
10.1038/nmeth.2083
10.1038/nmeth.2083 · doi-reference
Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer
10.1016/j.media.2020.101915 · doi-reference
10.1371/journal.pone.0242355
10.1371/journal.pone.0242355 · doi-reference
10.21203/rs.3.rs-78130/v1
10.21203/rs.3.rs-78130/v1 · doi-reference
Misdiagnosis of babesiosis as malaria, Equatorial Guinea
10.3201/eid2408.180180 · doi-reference
10.1016/j.mib.2016.08.004
10.1016/j.mib.2016.08.004 · doi-reference
Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images
10.7717/peerj.6977 · doi-reference
Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images
10.7717/peerj.4568 · doi-reference
Applications of Digital Microscopy and Densely Connected Convolutional Neural Networks for Automated Quantification of Babesia-Infected Erythrocytes
10.1093/clinchem/hvab237 · doi-reference
10.1002/cyto.a.24321
10.1002/cyto.a.24321 · doi-reference
Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears
10.1109/jbhi.2019.2939121 · doi-reference
An Effective Convolutional Neural Network for Classifying Red Blood Cells in Malaria Diseases
10.1007/s12539-020-00367-7 · doi-reference
Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears
10.1109/jbhi.2020.3034863 · doi-reference
Protective immunity to liver‐stage malaria
10.1038/cti.2016.60 · doi-reference