scholarly journals Deteksi Malaria Berbasis Segmentasi Warna Citra dan Pembelajaran Mesin

2021 ◽  
Vol 8 (4) ◽  
pp. 769
Author(s):  
Agung W. Setiawan ◽  
Yusuf A. Rahman ◽  
Amir Faisal ◽  
Marsudi Siburian ◽  
Nova Resfita ◽  
...  
Keyword(s):  
Machine Learning ◽  
World Health Organization ◽  
Detection Method ◽  
World Health ◽  
Segmented Image ◽  
S 100 ◽  
Object Counting ◽  
The Government ◽  
Health Organization ◽  
Computational Resources

<p class="Abstrak">Di beberapa daerah di Indonesia, malaria masih merupakan salah satu penyakit endemik dan termasuk ke dalam kategori penyakit menular dengan vektor nyamuk <em>Anopheles</em>. Penurunan jumlah mortalitas penderita malaria ini telah menjadi program Pemerintah Indonesia dan <em>World Health Organization</em>. Salah satu hal penting yang dapat dilakukan adalah menyediakan alat diagnosis malaria yang cepat dan akurat berbantukan komputer. Oleh karena itu, pada studi ini dikembangkan sebuah metode deteksi malaria berbasis segmentasi warna citra yang dikombinasikan dengan metode pencacahan objek citra dan pembelajaran mesin berbasis <em>Convolutional Neural Network</em>. Pada studi ini, segmentasi citra dilakukan dengan menetapkan suatu nilai ambas batas tertentu (<em>thresholding</em>) pada model warna HSV. Nilai ambang batas untuk masing-masing kanal warna ditetapkan sebagai berikut: H = 100-175, S = 100-250, dan V = 60-190. Terdapat tiga skema pembelajaran mesin yang digunakan, yaitu citra asli menggunakan <em>RMSProp</em> <em>optimizer</em>, citra tersegmentasi menggunakan <em>RMSProp</em> dan <em>Adam</em> <em>optimizer</em>. Akurasi pelatihan dan validasi CNN tertinggi diperoleh dengan skema citra tersegmentasi menggunakan <em>RMSProp</em> <em>optimizer</em>, yaitu sebesar 92,77% dan 94,38%. Sementara, deteksi malaria berbasis pencacahan objek memiliki akurasi sebesar 93,78%. Meskipun deteksi malaria berbasis pencacahan objek memiliki akurasi 93,78%, tetapi sumber daya komputasi dan waktu yang diperlukan jauh lebih rendah.</p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="Abstrak"><em>Malaria is still one of the endemic diseases in several regions of Indonesia. Reducing the malaria mortality rate has become a notable programme, not only does the Government of the Republic of Indonesia project it, but also the World Health Organization has a similar plan to tackle this disease. One of the prominent concerns to properly promote this programme is providing a rapid and accurate malaria diagnosis tool by applying the computer-aided diagnostics to minimize human errors. The aim of this study is to develop a colour microscopic image-based malaria detection using object counting and CNN-based machine learning. In this research, the HSV colour model with threshold values of H: 100-175, S: 100-250, and V: 60-190 was used to remove the image background. There are three machine learning schemes implemented in this study, i.e. original image using RMSProp optimizer, segmented image using RMSProp and Adam optimizer. The highest training and validation accuracy of CNN were obtained using a segmented image scheme by the RMSProp optimizer, 0.9277 and 0.9438. On the contrary, object-based malaria detection has an accuracy of 93.78%. Furthermore, there are several considerations to determine the malaria detection method, i.e. accuracy, computational resources, and time. Even though malaria detection using object counting has an accuracy of 93.78%, lower than the accuracy of CNN validation, the computational resources and time required are much lower and faster. Therefore, this detection method is suitable for smartphone-based devices with low-middle end specifications.</em></p>

Team Rubicon Medical Response to Hurricane Dorian in the Bahamas

2019 ◽  
Vol 13 (5-6) ◽  
pp. 1086-1089
Author(s):  
Andrew J. Bouland ◽  
Jordan Selzer ◽  
Madi Yogman ◽  
David W. Callaway
Keyword(s):  
World Health Organization ◽  
World Health ◽  
Medical Team ◽  
The Bahamas ◽  
Emergency Medical Team ◽  
Medical Response ◽  
Medical Clinics ◽  
The Government ◽  
Health Organization

ABSTRACTOn September 1, 2019, Hurricane Dorian made landfall as a category 5 hurricane on Great Abaco Island, Bahamas. Hurricane Dorian matched the “Labor Day” hurricane of 1935 as the strongest recorded Atlantic hurricane to make landfall with maximum sustained winds of 185 miles/h.1 At the request of the Government of the Bahamas, Team Rubicon activated a World Health Organization Type 1 Mobile Emergency Medical Team and responded to Great Abaco Island. The team provided medical care and reconnaissance of medical clinics on the island and surrounding cays…

scholarly journals Strategies for prevention and control of COVID-19 in Nepal

2020 ◽  
Vol 7 (1) ◽  
pp. 85-88 ◽  
Author(s):  
Kiran Sapkota ◽  
Ganesh Dangal ◽  
Madhu Koirala ◽  
Kalyan Sapkota ◽  
Asmita Poudel ◽  
...  
Keyword(s):  
World Health Organization ◽  
Prevention And Control ◽  
Preventive Measures ◽  
Large Population ◽  
World Health ◽  
The World ◽  
Community Transmission ◽  
The Government ◽  
Health Organization ◽  
And Control

Coronavirus disease (COVID-19) outbreak, caused by the most recently discovered coronavirus, is currently affecting a large population across the globe. World health organization (WHO) has already declared COVID-19, a pandemic, and the world is fighting to contain the COVID-19 outbreak. Nepal has taken several preventive measures to control the coronavirus outbreak. However, some additional steps are needed to prevent community transmission of the disease. This brief communication discusses the government of Nepal actions and provides recommendations for the prevention and control of COVID-19 infection in Nepal.

scholarly journals Gambaran Kejadian Malaria Pada Ibu Hamil di Rumah Sakit Umum Daerah Kabupaten Boven Digoel Papua

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Halmina Ilyas ◽  
Serly Serly
Keyword(s):  
Data Analysis ◽  
Pregnant Women ◽  
World Health Organization ◽  
Malaria Infection ◽  
District General Hospital ◽  
World Health ◽  
Maternal Deaths ◽  
The World ◽  
The Government ◽  
Health Organization

In malaria endemic areas, pregnant women are more susceptible to infection with malaria parasites than non-pregnant women. The World Health Organization (WHO) in 2014 estimated that 10,000 maternal deaths each year were associated with malaria infection during pregnancy. The aim of the study was to describe the incidence of malaria in pregnant women at the Boven Digoel District General Hospital, Papua. Methods This research uses a descriptive type of research. Samples were taken as many as 92 pregnant women who were taken by accidental sampling. Collecting data by using a questionnaire sheet. Data analysis was carried out univariate and bivariate. The results showed that from 78 pregnant women who were positive for malaria, most of them suffered from anemia as many as 51 people (65.4%) and 27 people did not suffer from anemia (34.6%). For the incidence of abortion from 78 pregnant women who were positive for malaria, most of them did not experience an abortion as many as 62 people (79.5%) and 16 people had an abortion (20.5%). For the habit of being out of the house at night, from 78 pregnant women who were positive for malaria, most of them were always outside at night as many as 41 people (52.6%) and 37 people (47 people) were not out of the house at night. ,4%). The conclusion of this study, the description of the incidence of malaria in pregnant women mostly suffer from anemia, do not have abortions and are always outside the house at night. The advice that can be given is that malaria in pregnant women must be eradicated immediately so that the MCH program made by the government can be successful and the health of pregnant women can be maintained

Dealing with a Pandemic of Misinformation

BioMedica ◽  
2020 ◽  
Vol 36 (2S) ◽  
pp. 26-27
Author(s):  
Muhammad Atif
Keyword(s):  
Mass Media ◽  
Social Responsibility ◽  
World Health Organization ◽  
Science And Technology ◽  
Corrective Action ◽  
High Time ◽  
World Health ◽  
Conspiracy Theories ◽  
The Government ◽  
Health Organization

<p>After World Health Organization named COVID-19 pandemic as a &ldquo;Pandemic of Misinformation&rdquo;, a common man has to cope with superfluous advices, remedies and, most of all, conspiracy theories, that seem undermining even the genuine recommendations of experts and authorities. This is a high time that timely corrective action, preaching social responsibility, relying on science and technology, and using mass media as channels to communicate the truth, may be used as weapons by the government in the battle against COVID-19 infodemic.</p>

Deteksi Masker Pencegahan Covid19 Menggunakan Convolutional Neural Network Berbasis Android

2021 ◽  
Vol 5 (3) ◽  
pp. 576-583
Author(s):  
Purnama Nyoman ◽  
Putu Kusuma Negara
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Gradient Descent ◽  
Detection Method ◽  
World Health ◽  
The Public ◽  
Network Method ◽  
Public Areas ◽  
The Government ◽  
Health Organization

Masks are an important part of preventing Covid19 disease.The World Health Organization (WHO) have also recommended  the community use masks when doing activities in public areas. There are many types of masks that are used to cover the nose and mouth.  In general, there are about 3 types of masks that are commonly used by the public today, namely medical masks, N95 and cloth masks. This study aims to detect the type of mask used by the community. So that it can make easier for the government to apply discipline in COVID-19 health protocol. The detection method used in this study is a convolutional neural network (CNN). The first step is acquisition of knowledge, which first collects the types of masks on the market, followed by the representation of that knowledge before being modeled into a mathematical calculation formula, which will then be processed using the Convolutional Neural Network method. The system will be carried out by analyzing the recall value, its precision and accuracy.Testing process is carried out on an Android-based device  and the mobilenetV2 framework. In this study, the accuracy value is 90% using ADAM Optimization and 80 % using Gradient descent optimization.

scholarly journals A Survey on Recent Advances in Wearable Fall Detection Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Anita Ramachandran ◽  
Anupama Karuppiah
Keyword(s):  
Machine Learning ◽  
World Health Organization ◽  
Fall Detection ◽  
Healthcare Systems ◽  
World Health ◽  
The European Union ◽  
Human Beings ◽  
Average Life Expectancy ◽  
Detection Systems ◽  
Health Organization

With advances in medicine and healthcare systems, the average life expectancy of human beings has increased to more than 80 yrs. As a result, the demographic old-age dependency ratio (people aged 65 or above relative to those aged 15–64) is expected to increase, by 2060, from ∼28% to ∼50% in the European Union and from ∼33% to ∼45% in Asia (Ageing Report European Economy, 2015). Therefore, the percentage of people who need additional care is also expected to increase. For instance, per studies conducted by the National Program for Health Care of the Elderly (NPHCE), elderly population in India will increase to 12% of the national population by 2025 with 8%–10% requiring utmost care. Geriatric healthcare has gained a lot of prominence in recent years, with specific focus on fall detection systems (FDSs) because of their impact on public lives. According to a World Health Organization report, the frequency of falls increases with increase in age and frailty. Older people living in nursing homes fall more often than those living in the community and 40% of them experience recurrent falls (World Health Organization, 2007). Machine learning (ML) has found its application in geriatric healthcare systems, especially in FDSs. In this paper, we examine the requirements of a typical FDS. Then we present a survey of the recent work in the area of fall detection systems, with focus on the application of machine learning. We also analyze the challenges in FDS systems based on the literature survey.

World Health Organization

1954 ◽  
Vol 8 (2) ◽  
pp. 270-273
Keyword(s):  
World Health Organization ◽  
Program Analysis ◽  
Technical Assistance ◽  
Essential Element ◽  
World Health ◽  
Director General ◽  
Health Administration ◽  
Minimum Requirements ◽  
The Government ◽  
Health Organization

At its thirteenth session, which was held in Geneva from January 12 to February 2, 1954, the Executive Board of the World Health Organization had some 80 items on its agenda. It examined a) reports on the work of expert and special committees concerned with such subjects as malaria, poliomyelitis, rabies, drugs liable to produce addiction, bioligical standardization, environmental sanitation, alcohol, public-health administration, rheumatic diseases, quarantine measures, and yellow fever; b) progress being made in a number of projects, such as a campaign against smallpox, the selection of international non-proprietary names for drugs, standardization of laboratory tests of foods, and a study on international medical law; and c) a variety of administrative and financial matters, including the Director-General's proposed program and budget estimates for 1955, the scale of assessments for member countries, and the revision of the staff rules proposed by the Director-General. Decisions taken by the Board included a recommendation that the seventh World Health Assembly request the Board at its fifteenth session to continue the study of program analysis and evaluation and report to the eighth Assembly, concurrence in certain transfers proposed by the Director-General between sections of the 1954 appropriation resolution of the sixth Assembly, and recommendations as to the procedure for considering the 1955 program and budget estimates at the seventh Assembly. Noting that the financial problems facing WHO in implementing the 1954 program arose because the known amount of technical assistance funds to be made available to the organization in 1954 fell substantially short of amounts expected and was inadequate to meet the minimum requirements, the Board authorized the Director-General to: continue all projects and activities then in operation, implement those projects not yet started where the government concerned had proceeded to the extent that funds spent or set aside would be lost if the project did not go forward or where the project was an essential element of a program planned in stages which had been agreed with WHO and the government concerned, defer starting new activities wherever possible, and report to the seventh Assembly on further developments.

scholarly journals IMPLEMENTASI NILAI-NILAI PANCASILA DALAM ERA “NEW NORMAL”

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Sri Mirnawati
Keyword(s):  
World Health Organization ◽  
Community Resilience ◽  
World Health ◽  
National Interests ◽  
New Normal ◽  
The Face ◽  
The Government ◽  
Life Philosophy ◽  
Health Organization

The Covid-19 pandemic that Indonesia has been facing since March 2020 requires well-planned handling to deal with this new normal or new normal. Adopt health protocols that are in accordance with World Health Organization (WHO) directives that apply globally to strengthen community resilience in the face of the Covid-19 pandemic. Through various policies that have been established by the Government of Indonesia to respond to this Covid-19 pandemic health disaster. The level of transmission and spread of Covid-19 is still increasing and there has not been a significant decrease because the implementation of policies that handle Covid-19 which refers to WHO directives are still faced with many problems so that the handling is still not optimal and effective. Therefore, it is necessary to change the approach to handling the Covid-19 pandemic which is based on the values of Pancasila as a view of the life philosophy of the nation and the Indonesian people when viewed from the perspective of national interests, which is expected to increase the useful results of the efforts to handle the Covid-19 pandemic carried out by the Government. The implementation of Pancasila values in handling the Covid-19 pandemic can create a new normal or a new normal that is free from Covid-19.

scholarly journals COVID-19: Easing the coronavirus lockdowns with caution

2020 ◽  
Author(s):  
Rasheed Omobolaji Alabi ◽  
Akpojoto Siemuri ◽  
Mohammed Elmusrati
Keyword(s):  
World Health Organization ◽  
Forecast Model ◽  
World Health ◽  
The Novel ◽  
Forecasting Accuracy ◽  
The World ◽  
The Government ◽  
Health Organization ◽  
Second Wave ◽  
Death Cases

Background: The spread of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has reached a global level, creating a pandemic. The government of various countries, their citizens, politicians, and business owners are worried about the unavoidable economic impacts of this pandemic. Therefore, there is an eagerness for the pandemic peaking. Objectives: This study uses an objective approach to emphasize the need to be pragmatic with easing of lockdowns measures worldwide through the forecast of the possible trend of COVID-19. This is necessary to ensure that the enthusiasm about SARS-CoV-2 peaking is properly examined, easing of lockdown is done systematically to avoid second-wave of the pandemic. Methods: We used the Facebook prophet on the World Health Organization data for COVID-19 to forecast the spread of SARS-CoV-2 for the 7th April until 3rd May 2020. The forecast model was further used to forecast the trend of the virus for the 8th until 14th May 2020. We presented the forecast of the confirmed and death cases. Results: Our findings from the forecast showed an increase in the number of new cases for this period. Therefore, the need for easing the lockdown with caution becomes imperative. Our model showed good performance when compared to the official report from the World Health Organization. The average forecasting accuracy of our model was 79.6%. Conclusion: Although, the global and economic impact of COVID-19 is daunting. However, excessive optimism about easing the lockdown should be appropriately weighed against the risk of underestimating its spread. As seen globally, the risks appeared far from being symmetric. Therefore, the forecasting provided in this study offers an insight into the spread of the virus for effective planning and decision-making in terms of easing the lockdowns in various countries.

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