Myat Htoo Linn

Based on my previous discussion and study, the endemic model of malaria transmission considered SIR in the human population and SI in the mosquito population. The vector component of the model does not include an immune class as mosquitoes never recover from the infection. The immune class in the mosquito population is negligible and natural death…[Read more]

Thanks, Ajarn! I am aware of suicide as an act of behavior rather than a disease and wanted to know how the modeling can help in predicting the suicidal risks and outcomes. Let me add Malaria to the discussion, already been completed for week 2 discussion on the model structure.

Malaria is one of the greatest historical killers of mankind,…[Read more]

I am interested in the impact of population movement/migration/human mobility and malaria transmission. People move for a number of reasons, including environmental deterioration, economic necessity, conflicts, and natural disasters. Identifying and understanding the influence of these population movements can improve prevention measures and…[Read more]

Sorry for my late discussion Friend!
1. To improve the syphilis surveillance system at Tak Hospital, I would emphasize mainly the coordination between the different work units within the hospital. The officers from the health screening unit and different professionals from the STI/HIV clinic, blood bank, ANC clinic, and laboratory work closely to…[Read more]

I am personally interested in exploring the suicide risks around us, especially among youth in my country. I am also quite aware of suicide as an act of behavior rather than a disease but by associating it with various underlying factors such as depression, physiological stress, political driving forces, social factors, etc., modeling the suicide…[Read more]

Yes, Toby!
I also got the same map of Local Moran’s I as yours which differs from the video.
Maybe this could be the cause of the raw data set for which cannot revise it?

Thanks all bros!!
You are life saviours.
I am also resolved.

1. I think the author is interested in investigating the suicide problem in Thailand due to reasons of unique socio-economic landscape with limited research at the micro level which differs from developed nations. A substantial portion of the Thailand population is engaged in agriculture, which is why agrarian employment is present in the research…[Read more]

1. Implementing AI technologies in epidemic surveillance systems can be transformative in low-resource settings. Using AI can overcome the limitations of weak health infrastructure by processing open-source data from social media and news reports to detect early signs of disease outbreaks. To enhance these systems, the application of mobile…[Read more]

1. What are possible reasons locations in epidemiological research have not been incorporated as much as other components in epidemiological research? How can spatial epidemiology be considered as an interdisciplinary science?

As I can understand from reading the assigned papers, one reason is the limited incorporation of the places in…[Read more]

1. As the colleagues discussed, the decision tree model can be integrated into the clinical decision support system which can greatly assist surgeons in preoperative planning and decision-making. It can analyze a patient’s preoperative characteristics and predict potential complications, such as massive intraoperative blood loss, as demonstrated…[Read more]

1. With the limited digital infrastructure and resource constraints, I didn’t see the electronic-based clinical decision support system specifically using or plan to use for NCD patients in Myanmar. One of my friends said there is one application called the Community-Based Health Assistance app which is using in MAM (Medical Action Myanmar) at t…[Read more]

1. I favor the interdisciplinary collaboration among a diverse team of experts and continuous education of users is important to improve the safety of medical AI systems. All of the stakeholders like clinicians, data scientists, and patient representatives can work together as clinicians can understand the rationale behind AI decisions, data…[Read more]

I truly appreciate your fantastic presentation, Teeraboon! We learned further understanding.

1. I would consider incorporating additional physiological data could be beneficial. Integrating real-time data might provide a more comprehensive picture of the patient’s status during anesthesia induction. Additionally, continuous blood pressure…[Read more]

Thanks much for sharing the paper on the machine learning approach and the wonderful presentation, Toby!

1. I have no more additions for the stakeholders to the colleagues’ discussions previously. This should just be patient-centric perspectives in applying machine learning to symptom prediction. I would love to focus on regulatory bodies and e…[Read more]

Hello Sirithep!
Thank you so much for sharing your final project.
This is much appreciated for your work, I especially liked the use of color and clarity in your dashboard presentation. The simplicity effectively captures attention and enhances our pre-attentive processing of the COVID-19 data.
I have two comments I would like to discuss with you.…[Read more]

Hello!
Let me share mine and you may check here!
https://lookerstudio.google.com/reporting/7b04cfb5-d14e-4be0-bbd5-82b8014d3bdc

I have used features that could simply summarize the COVID-19 information at a glance in the main dashboard.
The scorecard was used with chunking and color theme which may bring up your short-term/working memory. Other…[Read more]

Dear Ajarn/Friends! Let me share mine!

Please kindly check the link here!
1. https://snipboard.io/5hia2Z.jpg
2. https://snipboard.io/Zvcx9j.jpg
3. https://snipboard.io/vFDVfz.jpg
4. https://snipboard.io/589XQ6.jpg
5. https://snipboard.io/Sq9cin.jpg
6. https://snipboard.io/1DWN0n.jpg
7. https://snipboard.io/WkjVws.jpg

Direct link to…[Read more]

Hello Nichcha! Thanks for sharing the JHU’s COVID-19 dashboard with us. I also support your preference for a user-friendly design and using the bubble chart to present higher-lower numbers with the bubble size. I also like it can navigate from sheet to sheet easily to see different information on Incidence rate, CFR, Vaccinations, etc. I consider…[Read more]

I would like to share the following COVID-19 dashboard that was created by a group of contributors led by one medical doctor during the COVID-19 crisis in Myanmar around 2020-2022. The data were extracted from the Ministry of Health and Sport (MoHS), Myanmar’s daily announcement, and worked with the Google Data Studio (current Looker Studio) at t…[Read more]