Generative AI-Driven Decision-Making for Disease Control and Pandemic Preparedness Model 4.0 in Rural Communities of Bangladesh: Management Informatics Approach DOI Creative Commons
Mohammad Saddam Hosen, MD Shahidul Islam Fakir,

Shamal Chandra Hawlader

и другие.

European Journal of Medical and Health Research, Год журнала: 2025, Номер 3(2), С. 104 - 121

Опубликована: Март 20, 2025

Rural Bangladesh is confronted with substantial healthcare obstacles, such as inadequate infrastructure, information systems, and restricted access to medical personnel. These obstacles impede effective disease control pandemic preparedness. This investigation employs a structured methodology develop analyze numerous plausible scenarios systematically. A purposive sampling strategy was implemented, which involved the administration of questionnaire survey 264 rural residents in Rangamati district completion distinct by 103 The impact effectiveness study are assessed through logistic regression analysis pre-post comparison that Wilcoxon Signed-Rank test Kendall's coefficient for non-parametric paired categorical variables. evaluates evolution preparedness prior subsequent implementation Generative AI-Based Model 4.0. results indicate trust AI (β = 1.20, p 0.020) confidence sharing health data 9.049, most significant predictors adoption. At same time, infrastructure limitations digital constraints continue be constraints. concludes resilience marginalized populations can improved AI-driven, localized strategies. integration into systems offers transformative opportunity, but it contingent upon active community engagement, enhanced literacy, strong government involvement.

Язык: Английский

Human versus Artificial Intelligence: ChatGPT-4 Outperforming Bing, Bard, ChatGPT-3.5 and Humans in Clinical Chemistry Multiple-Choice Questions DOI Creative Commons
Malik Sallam,

Khaled Al‐Salahat,

Huda Eid

и другие.

Advances in Medical Education and Practice, Год журнала: 2024, Номер Volume 15, С. 857 - 871

Опубликована: Сен. 1, 2024

Artificial intelligence (AI) chatbots excel in language understanding and generation. These models can transform healthcare education practice. However, it is important to assess the performance of such AI various topics highlight its strengths possible limitations. This study aimed evaluate ChatGPT (GPT-3.5 GPT-4), Bing, Bard compared human students at a postgraduate master's level Medical Laboratory Sciences.

Язык: Английский

Процитировано

6

Development and Evaluation of an AI-Assisted Answer Assessment (4A) for Cognitive Assessments in Nursing Education DOI Creative Commons
Piyanut Xuto, Piyaporn Prasitwattanaseree, Tareewan Chaiboonruang

и другие.

Nursing Reports, Год журнала: 2025, Номер 15(3), С. 80 - 80

Опубликована: Фев. 26, 2025

Artificial intelligence (AI) can potentially enhance cognitive assessment practices in maternal and child health nursing education. Objectives: To evaluate the reliability, accuracy precision, external validity of an AI-assisted answer (4A) program for assessments Methods: This study is a validation study. Initially, 170 students from northern Thailand participated, with 52 randomly selected detailed testing. Agreement testing between 4A human experts was conducted using intraclass correlation coefficient (ICC). Accuracy precision compared scores expert via McNemar test. External involved 138 participants to compare program’s against national examination outcomes logistic regression. Results: Results indicated high level consistency (ICC = 0.886). With 0.808 0.913, expert’s 0.923 1.000. The test (χ2 0.4, p 0.527) showed no significant difference evaluation performance AI experts. Higher on significantly predicted success (OR: 1.124, 0.031). Conclusions: demonstrates potential reliably assessing students’ abilities predicting exam success. advocates continued integration educational importance refining systems better align traditional methods.

Язык: Английский

Процитировано

0

The performance of OpenAI ChatGPT-4 and Google Gemini in virology multiple-choice questions: a comparative analysis of English and Arabic responses DOI Creative Commons
Malik Sallam,

Kholoud Al-Mahzoum,

Rawan Ahmad Almutawaa

и другие.

BMC Research Notes, Год журнала: 2024, Номер 17(1)

Опубликована: Сен. 3, 2024

Язык: Английский

Процитировано

4

Generative AI-Driven Decision-Making for Disease Control and Pandemic Preparedness Model 4.0 in Rural Communities of Bangladesh: Management Informatics Approach DOI Creative Commons
Mohammad Saddam Hosen, MD Shahidul Islam Fakir,

Shamal Chandra Hawlader

и другие.

European Journal of Medical and Health Research, Год журнала: 2025, Номер 3(2), С. 104 - 121

Опубликована: Март 20, 2025

Rural Bangladesh is confronted with substantial healthcare obstacles, such as inadequate infrastructure, information systems, and restricted access to medical personnel. These obstacles impede effective disease control pandemic preparedness. This investigation employs a structured methodology develop analyze numerous plausible scenarios systematically. A purposive sampling strategy was implemented, which involved the administration of questionnaire survey 264 rural residents in Rangamati district completion distinct by 103 The impact effectiveness study are assessed through logistic regression analysis pre-post comparison that Wilcoxon Signed-Rank test Kendall's coefficient for non-parametric paired categorical variables. evaluates evolution preparedness prior subsequent implementation Generative AI-Based Model 4.0. results indicate trust AI (β = 1.20, p 0.020) confidence sharing health data 9.049, most significant predictors adoption. At same time, infrastructure limitations digital constraints continue be constraints. concludes resilience marginalized populations can improved AI-driven, localized strategies. integration into systems offers transformative opportunity, but it contingent upon active community engagement, enhanced literacy, strong government involvement.

Язык: Английский

Процитировано

0