Myat Htoo Linn

Thank you so much friends for all of your valuable discussion.
I have noted all of your comments which can be considered in future research around health information dissemination.

1) The findings of the article on the use of ePROs can be highly beneficial in various healthcare settings where ongoing symptom monitoring is crucial for effective treatment. It would be highly useful in mental health conditions like depression, anxiety, and bipolar disorder because these symptoms can fluctuate over time and are difficult to…[Read more]

1) By integrating environmental data in the malaria outbreak predictions, the first thing I am sure is it will improve the spatial and temporal precision. The reason is that environmental data often provides continuous, real-time monitoring of conditions across large areas. I believe this will allow for more geographically specific and timely…[Read more]

1) There are lots of challenges such as funding and technology constraints, interoperability, regularity compliance, user adoption, workforce capacity, etc., especially in developing countries for the sustainability of health information systems. Based on my experience, the lack of interest of the decision-maker in the system development is the…[Read more]

Thank you so much for the brilliant presentation of this information, Ko Pyae. I would like to share some of my opinions;
1) This is sure the different demographic information will have various influences on the perceived ease of use and usefulness of the e-health applications. For Age, no doubt that young age, who are often tech-savvy will be…[Read more]

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]