chanapong

1. While the WHO “building blocks” framework is a familiar tool, it is frequently criticized as being not ideal for conflict-affected settings because it oversimplifies complex, dynamic health systems. Relying on these standard components often results in a failure to assess context-specific factors like resilience and the impact of violence,…[Read more]

1. The primary strength of using only basic survey data is that these variables are easy to obtain, inexpensive, and do not require specialized equipment or laboratory investigations, such as HbA1c testing, ophthalmoscopic examination, or urinary microalbumin analysis. This approach facilitates large-scale data collection and enhances feasibility…[Read more]

Discussion point 1
User outcomes, particularly system usability, should be included to assess the challenges reporting officers faced during data collection. Furthermore, data quality metrics should be reported to evaluate the completeness and integrity of the data input by staff.

Discussion point 2
A small-scale controlled study is suitable when…[Read more]

1. What are the ethical implications of removing the requirement for physical presence during consent?
There are several ethical considerations when implementing e-ICF without the physical presence of staff. First, participants with low digital literacy may struggle to use electronic devices properly. Second, they may find it difficult to…[Read more]

1.The types of acceptable data depend heavily on country regulations and personal consent. In my perspective, health status (such as a confirmed positive case) can be collected, provided it is kept private and measures are taken to prevent identity leakage. Additionally, Bluetooth proximity data or GPS location can be collected to improve the…[Read more]

Q1. Given regulations like GDPR (“right to be forgotten”), can a blockchain technology based on immutability (the inability to delete) ever be fully compliant with healthcare privacy laws?
The GDPR ‘right to be forgotten’ generally does not apply to healthcare due to legal and medical necessity exemptions, as well as the difficulties posed by the…[Read more]

1. How does this study challenge the traditional use of weather-station data (temperature) in vector models?
This study challenges predictive models that use ambient temperature to estimate vector populations at various stages by comparing them with microclimatic temperatures recorded inside storm drains. Storm drains, which reflect the…[Read more]

I have a question about the study titled “Association rule mining to detect factors that contribute to heart disease in males and females” which was an example in association rule mining. Why did the authors use a machine learning method to identify disease-related factors instead of a traditional statistical method such as logistic reg…[Read more]

Thank you for your response; it has significantly helped me better understand the concept.

From my understanding, machine learning tends to offer stronger predictive power but is generally limited in its ability to explain relationships between variables. In contrast, statistical models are better suited for interpreting the relationships and…[Read more]

I have one more question about how to choose a model for machine learning. Should the choice be based on clinical statistics and the type of prediction outcome, such as disease prediction (yes or no) or prognosis (good or bad)? For example, should logistic regression be used for these kinds of binary outcomes?

Thanks for your answer. It really helped me better understand the concept of the Bayesian network model.

While working on Assignment 2, I had a question about why variables like NS1 or WBC are not parent nodes of the dengue outcome, even though the objective of the network is to predict the probability of dengue outcome.

Thank Aj.Chawarat for the clarification regarding the assignments. I understand that there are 9 participants enrolled in this course. However, I am not sure who is taking the course for credit or audit, and I also do not know how to contact the other students.

May I kindly ask for your assistance in this matter? Perhaps you could help…[Read more]

Thanks for sharing, Cing. I also agree with you regarding the designation of vaccination changes as acceptable, since these changes do not directly alter the health record, and they are typically made in advance with proper notifications sent to users. Such changes may be due to vaccination stock management or other operational reasons. Therefore,…[Read more]

3. What factors influence user satisfaction with vaccination apps?
User satisfaction with vaccination apps is influenced by five key factors: content, functionality, user experience, service attitude, and privacy. Among these, privacy emerged as the most critical issue, with results indicating that users were particularly dissatisfied with how…[Read more]

Thank you for sharing this comment. I agree with you that studying cross-border mobility and hospitalization can provide valuable insights. However, individuals with asymptomatic or mild symptoms may be missed or underrepresented in such studies. Furthermore, examining the movement patterns of healthcare and government officials could also be an…[Read more]

1. What are potential follow-up studies on mobility patterns?
A potential follow-up study on cross-border mobility is intercountry disease transmission.

2. How did government restrictions affect mobility patterns?
Government restrictions reduced individual mobility, including cross-border movement, as demonstrated by the decrease in travel…[Read more]

In my opinion,email reminders can have dual effects, potentially increasing or decreasing the response rate. While they often serve as helpful prompts that improve participation, excessive or poorly timed reminders may lead to reminder fatigue, annoyance, or disengagement, ultimately reducing the likelihood of response—especially among users who f…[Read more]