scholarly journals Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Matthew P. Horning ◽  
Charles B. Delahunt ◽  
Christine M. Bachman ◽  
Jennifer Luchavez ◽  
Christian Luna ◽  
...  
Keyword(s):  
Case Management ◽  
Malaria Parasite ◽  
Diagnostic System ◽  
Malaria Diagnosis ◽  
Drug Efficacy ◽  
Automated System ◽  
World Health ◽  
Detection Accuracy ◽  
Diagnostic Systems ◽  
Fully Automated System

Abstract Background Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibility of field microscopy. The World Health Organization (WHO) has designed a 55-slide set (WHO 55) for their External Competence Assessment of Malaria Microscopists (ECAMM) programme, which can also serve as a valuable benchmark for automated systems. The performance of a fully-automated malaria diagnostic system, EasyScan GO, on a WHO 55 slide set was evaluated. Methods The WHO 55 slide set is designed to evaluate microscopist competence in three areas of malaria diagnosis using Giemsa-stained blood films, focused on crucial field needs: malaria parasite detection, malaria parasite species identification (ID), and malaria parasite quantitation. The EasyScan GO is a fully-automated system that combines scanning of Giemsa-stained blood films with assessment algorithms to deliver malaria diagnoses. This system was tested on a WHO 55 slide set. Results The EasyScan GO achieved 94.3 % detection accuracy, 82.9 % species ID accuracy, and 50 % quantitation accuracy, corresponding to WHO microscopy competence Levels 1, 2, and 1, respectively. This is, to our knowledge, the best performance of a fully-automated system on a WHO 55 set. Conclusions EasyScan GO’s expert ratings in detection and quantitation on the WHO 55 slide set point towards its potential value in drug efficacy use-cases, as well as in some case management situations with less stringent species ID needs. Improved runtime may enable use in general case management settings.

scholarly journals Ten Years of Universal Testing: How the Rapid Diagnostic Test Became a Game Changer for Malaria Case Management and Improved Disease Reporting

2021 ◽  
Author(s):  
Michael Aidoo ◽  
Sandra Incardona
Keyword(s):  
Case Management ◽  
Health System ◽  
Malaria Control ◽  
Malaria Case ◽  
Health Workers ◽  
Malaria Diagnosis ◽  
World Health ◽  
Smear Microscopy ◽  
Malaria Case Management ◽  
Laboratory Staff

In 2010, the World Health Organization changed its guidance on malaria case management, recommending parasitological confirmation of all suspected cases before treatment with an antimalarial. This recommendation was in large part as a result of the availability of quality assured malaria rapid diagnostic tests (RDTs) that made it possible for malaria diagnosis to be performed by laboratory staff in all health facilities irrespective of the facility’s place in the tiered health system. Community health workers and other non-laboratory health workers who traditionally did not perform malaria testing due to the technical and logistic demands of smear microscopy were now able to test for malaria. The use of RDTs has led to substantial increases in testing rates, improved quality of case management, as well as more accurate reporting of malaria cases. Although current RDTs have limitations, they remain one of the most important tools in contemporary malaria control. Further improvements to existing products, such as increased sensitivity for non-falciparum tests, diversification of Plasmodium falciparum antigen targets, along with strengthened health system support for current RDTs will further enhance their utility in malaria control and prevention.

The Application of Machine Learning Technique for Malaria Diagnosis

2010 ◽  
Vol 1 (1) ◽  
pp. 68-77 ◽  
Author(s):  
C. Ugwu ◽  
N. L Onyejegbu ◽  
I. C Obagbuwa
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Knowledge Base ◽  
User Interfaces ◽  
Healthcare Delivery ◽  
Diagnostic System ◽  
Malaria Diagnosis ◽  
World Health ◽  
Machine Learning Technique ◽  
Learning Technique

Healthcare delivery in African nations has long been a worldwide issue, which is why the United Nations and World Health Organization seek for ways to alleviate this problem and thereby reduce the number of lives that are lost every year due to poor health facilities and inadequate health care administration. Healthcare delivery concerns are most predominant in Nigeria and it became imperatively clear that the system of medical diagnosis must be automated. This paper explores the potential of machine learning technique (decision tree) in development of a malaria diagnostic system. The decision tree algorithm was used in the development of the knowledge base. Microsoft Access and Java programming language were used for database and user interfaces, respectively. During the diagnosis, symptoms are provided by the patient in the diagnostic system and a match is found in the knowledge base.

Fully Automated System for Aerobic or Anaerobic Sampling of Duodenal Digesta in Sheep or Cattle Equipped with Duodenal Reentrant Cannulas1

1985 ◽  
Vol 60 (5) ◽  
pp. 1359-1366 ◽  
Author(s):  
M. Ivan ◽  
D. J. Buckley ◽  
G. St. Amour ◽  
C. F. Nicholls ◽  
D. M. Veira
Keyword(s):  
Automated System ◽  
Fully Automated System

Evaluation of Various Diagnostic Techniques for the Diagnosis of Pulmonary and Extra Pulmonary Tuberculosis at a Tertiary Care Center in North India

2020 ◽  
Vol 20 (4) ◽  
pp. 433-439
Author(s):  
Monika Rajani ◽  
Molay Banerjee
Keyword(s):  
Care Center ◽  
Tertiary Care ◽  
Diagnostic System ◽  
Diagnostic Techniques ◽  
Automated System ◽  
North India ◽  
Mortality And Morbidity ◽  
Indicator Tube ◽  
Extra Pulmonary ◽  
Uv Lamp

Introduction: Tuberculosis (TB) is a one of the main causes of mortality and morbidity worldwide. Bactec MGIT (Mycobacteria Growth Indicator Tube) system is a rapid, reliable automated system for early diagnosis of pulmonary and extra pulmonary TB in setups where purchase of expensive instruments is not possible. The present study was thus carried out to evaluate AFB microscopy, culture on Lowenstein Jensen media and micro MGIT system for early and accurate diagnosis of Tuberculosis. Methods: A total of 280 samples were processed for direct AFB smear examination, and culture on micro MGIT and LJ media. The identification of Mycobacterium tuberculosis complex in positive cultures was done by MPT64 Ag card test (BD MGIT TBC Identification Test). Results: Out of the processed samples, (47.1%) 132/280 were positive for Mycobacterium spp by Micro MGIT, (35%) 98/280 on LJ medium and (25.7%) 72/280 by AFB smear. A total of (48.5%) 136 samples were positive by a combination of Micro MGIT and LJ medium. Among the total positive samples (136/280), Micro MGIT was found to be positive in 97% (132/136) of samples, LJ was positive in 72% (98/136), while 52.9% (72/136) were positive by AFB smear. Conclusion: Manual MGIT System is a simple and efficient, safe to use the diagnostic system. It does not require any expensive/special instrumentation other than the UV lamp for the detection of fluorescence. In areas with limited resources where the purchase of expensive instruments such as the MGIT 960 is out of scope, the use of manual MGIT for rapid susceptibility testing for MDR-TB could be an option. We would recommend testing MGIT 960 using first and secondline drugs to determine DST.

scholarly journals Significance of training, monitoring and assessment of malaria workers in achieving malaria elimination goal of Malaria Elimination Demonstration Project

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Harsh Rajvanshi ◽  
Sekh Nisar ◽  
Praveen K. Bharti ◽  
Himanshu Jayswar ◽  
Ashok K. Mishra ◽  
...  
Keyword(s):  
Case Management ◽  
Vector Control ◽  
Malaria Elimination ◽  
Disease Surveillance ◽  
Training Session ◽  
Central India ◽  
Malaria Diagnosis ◽  
Demonstration Project ◽  
National Goal ◽  
Health Delivery

Abstract Background The Malaria Elimination Demonstration Project (MEDP) maintained a workforce of 235 Village Malaria Workers (VMWs) and 25 Malaria Field Coordinators (MFCs) to conduct disease surveillance, case management, IEC/BCC activities, capacity building, and monitoring of vector control activities in 1233 villages of Mandla, a high malaria endemic district of Madhya Pradesh in central India. Methods The induction training was conducted for 3 days on malaria diagnosis, treatment, prevention, and ethics. All trainings were assessed using a pre and post-training assessment questionnaire, with 70% marks as qualifying threshold. The questionnaire was divided into three thematic areas viz. general knowledge related to malaria (KAP), diagnosis and treatment (DXRX), and vector control (PVC). Results In 2017, the project trained 330 candidates, followed by 243 and 247 candidates in 2018 and 2019, respectively. 94.3% candidates passed after a single training session. Almost all (95%) candidates showed improvement in knowledge after the training with 4% showing no effect and 1% showing deterioration. Progressive improvement in scores of 2017 cohort was seen along with significant improvement in performance of candidates in 2019 after the introduction of systematic monitoring and ‘shadowing’ training exercises. Conclusion The project has successfully demonstrated the value of recruitment of workers from the study area, outcome of training, and performance evaluation of field staff in malaria elimination programme. This careful strategy of recruitment and training resulted in a work-force that was capable of independently conducting surveillance, case management, vector control, and Information Education Communication/Behaviour Change Communication (IEC/BCC). The learnings of this study, including the training modules and monitoring processes, can be used to train the health delivery staff for achieving national goal for malaria elimination by 2030. Similar training and monitoring programmes could also be used for other public health delivery programmes.

scholarly journals Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Fetulhak Abdurahman ◽  
Kinde Anlay Fante ◽  
Mohammed Aliy
Keyword(s):  
Object Detection ◽  
Malaria Parasite ◽  
Blood Smear ◽  
Clustering Algorithm ◽  
State Of The Art ◽  
Detection Accuracy ◽  
Small Object ◽  
Thick Blood Smear ◽  
Malaria Parasites ◽  
Microscopic Images

Abstract Background Manual microscopic examination of Leishman/Giemsa stained thin and thick blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this method is that its accuracy, consistency, and diagnosis speed depend on microscopists’ diagnostic and technical skills. It is difficult to get highly skilled microscopists in remote areas of developing countries. To alleviate this problem, in this paper, we propose to investigate state-of-the-art one-stage and two-stage object detection algorithms for automated malaria parasite screening from microscopic image of thick blood slides. Results YOLOV3 and YOLOV4 models, which are state-of-the-art object detectors in accuracy and speed, are not optimized for detecting small objects such as malaria parasites in microscopic images. We modify these models by increasing feature scale and adding more detection layers to enhance their capability of detecting small objects without notably decreasing detection speed. We propose one modified YOLOV4 model, called YOLOV4-MOD and two modified models of YOLOV3, which are called YOLOV3-MOD1 and YOLOV3-MOD2. Besides, new anchor box sizes are generated using K-means clustering algorithm to exploit the potential of these models in small object detection. The performance of the modified YOLOV3 and YOLOV4 models were evaluated on a publicly available malaria dataset. These models have achieved state-of-the-art accuracy by exceeding performance of their original versions, Faster R-CNN, and SSD in terms of mean average precision (mAP), recall, precision, F1 score, and average IOU. YOLOV4-MOD has achieved the best detection accuracy among all the other models with a mAP of 96.32%. YOLOV3-MOD2 and YOLOV3-MOD1 have achieved mAP of 96.14% and 95.46%, respectively. Conclusions The experimental results of this study demonstrate that performance of modified YOLOV3 and YOLOV4 models are highly promising for detecting malaria parasites from images captured by a smartphone camera over the microscope eyepiece. The proposed system is suitable for deployment in low-resource setting areas.

scholarly journals Should Autism Spectrum Conditions Be Characterised in a More Positive Way in Our Modern World?

Medicina ◽  
2020 ◽  
Vol 56 (5) ◽  
pp. 233
Author(s):  
Barry Wright ◽  
Penny Spikins ◽  
Hannah Pearson
Keyword(s):  
Cognitive Abilities ◽  
World Health Organisation ◽  
Autism Spectrum ◽  
Classification Systems ◽  
World Health ◽  
Autism Spectrum Conditions ◽  
Modern World ◽  
Diagnostic Systems ◽  
Spectrum Condition ◽  
The Media

In a special issue that focuses on complex presentations related to Autism, we ask the question in this editorial whether an Autism Spectrum Condition without complexity is a disorder, or whether it represents human diversity? Much research into Autism Spectrum Conditions (ASCs) over the years has focused on comparisons between neuro-typical people and people with Autism Spectrum Conditions. These comparisons have tended to draw attention to ‘deficits’ in cognitive abilities and descriptions of behaviours that are characterised as unwanted. Not surprisingly, this is reflected in the classification systems from the World Health Organisation and the American Psychiatric Association. Public opinion about ASC may be influenced by presentations in the media of those with ASC who also have intellectual disability. Given that diagnostic systems are intended to help us better understand conditions in order to seek improved outcomes, we propose a more constructive approach to descriptions that uses more positive language, and balances descriptions of deficits with research finding of strengths and differences. We propose that this will be more helpful to individuals on the Autism Spectrum, both in terms of individual self-view, but also in terms of how society views Autism Spectrum Conditions more positively. Commentary has also been made on guidance that has been adjusted for people with ASC in relation to the current COVID-19 pandemic.

scholarly journals Evaluation of a New Immunochromatography Technology Test (LDBio Diagnostics) To Detect Toxoplasma IgG and IgM: Comparison with the Routine Architect Technique

2017 ◽  
Vol 55 (12) ◽  
pp. 3395-3404 ◽  
Author(s):  
Caroline Mahinc ◽  
Pierre Flori ◽  
Edouard Delaunay ◽  
Cécile Guillerme ◽  
Sana Charaoui ◽  
...  
Keyword(s):  
Western Blot ◽  
Sensitivity And Specificity ◽  
Blot Analysis ◽  
False Positive ◽  
Automated System ◽  
University Hospitals ◽  
Content Type ◽  
Automated Screening ◽  
Commercial Kits ◽  
Fully Automated System

ABSTRACTA study comparing the ICT (immunochromatography technology)ToxoplasmaIgG and IgM rapid diagnostic test (LDBio Diagnostics, France) with a fully automated system, Architect, was performed on samples from university hospitals of Marseille and Saint-Etienne. A total of 767 prospective sera and 235 selected sera were collected. The panels were selected to test various IgG and IgM parameters. The reference technique,ToxoplasmaIgGII Western blot analysis (LDBio Diagnostics), was used to confirm the IgG results, and commercial kits Platelia Toxo IgM (Bio-Rad) and Toxo-ISAgA (bioMérieux) were used in Saint-Etienne and Marseille, respectively, as the IgM reference techniques. Sensitivity and specificity of the ICT and the Architect IgG assays were compared using a prospective panel. Sensitivity was 100% for the ICT test and 92.1% for Architect (cutoff at 1.6 IU/ml). The low-IgG-titer serum results confirmed that ICT sensitivity was superior to that of Architect. Specificity was 98.7% (ICT) and 99.8% (Architect IgG). The ICT test is also useful for detecting IgM without IgG and is both sensitive (100%) and specific (100%), as it can distinguish nonspecific IgM from specificToxoplasmaIgM. In comparison, IgM sensitivity and specificity on Architect are 96.1% and 99.6%, respectively (cutoff at 0.5 arbitrary units [AU]/ml). To conclude, this new test overcomes the limitations of automated screening techniques, which are not sensitive enough for IgG and lack specificity for IgM (rare IgM false-positive cases).

scholarly journals Improving the Role and Contribution of Pharmacokinetic Analyses in Antimalarial Drug Clinical Trials

2014 ◽  
Vol 58 (10) ◽  
pp. 5643-5649 ◽  
Author(s):  
Katherine Kay ◽  
Eva Maria Hodel ◽  
Ian M. Hastings
Keyword(s):  
Antimalarial Drug ◽  
Theoretical Data ◽  
Drug Efficacy ◽  
Cost Effective ◽  
Field Studies ◽  
World Health ◽  
Efficacy Trials ◽  
Drug Concentrations ◽  
Health Organization ◽  
Study Designs

ABSTRACTIt is now World Health Organization (WHO) policy that drug concentrations on day 7 be measured as part of routine assessment in antimalarial drug efficacy trials. The rationale is that this single pharmacological measure serves as a simple and practical predictor of treatment outcome for antimalarial drugs with long half-lives. Herein we review theoretical data and field studies and conclude that the day 7 drug concentration (d7c) actually appears to be a poor predictor of therapeutic outcome. This poor predictive capability combined with the fact that many routine antimalarial trials will have few or no failures means that there appears to be little justification for this WHO recommendation. Pharmacological studies have a huge potential to improve antimalarial dosing, and we propose study designs that use more-focused, sophisticated, and cost-effective ways of generating these data than the mass collection of single d7c concentrations.

Ethical Issues Arising in Revising Classifications of Mental Disorders

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
N. Sartorius
Keyword(s):  
Mental Disorders ◽  
Ethical Issues ◽  
Task Force ◽  
Psychiatric Patients ◽  
World Health ◽  
Sufficient Evidence ◽  
Advisory Group ◽  
Diagnostic Systems ◽  
The World

The classification of mental disorders in the International Classification of Diseases (ICD) will be revised in the course of the next three years and its publication (as the 11th Revision of the ICD) will be published, after the approval of the World Health Assembly in 2014. In parallel, the American Psychiatric Association created a Task Force which has begun work on the proposals for the revision of its Diagnostic and Statistical Manual which is to be published as the DSM 5th Revision, in 2012. The World Health Organization has established a special advisory group that should assist it in developing proposals for the classification of mental disorders for the 11th Revision of the ICD and this group collaborates closely with the APA Task Force creating the DSM5 proposals.Numerous ethical issues arise in this process and need to be discussed now so as to inform the process of agreeing on the proposals for the new classifications. They include the importance of an internationally accepted classification as a protection against abuses of psychiatric patients; the need to set the threshold for the diagnosis of a mental disorder at a level ensuring that people with such disorders receive help, the need to avoid imposition of diagnostic systems or categories without sufficient evidence and others. The presentation will briefly discuss the process of constructing the proposals for the new classifications and ways in which the groups established by the WHO and the APA handle these ethical questions.

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