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Recent Submissions
From Cadaveric Dissection to Artificial Intelligence: A Chronological Review of Advances in Anatomy Education
(2025-12-02) Durongphan A.; Durongphan A.; Mahidol University
Cadaveric dissection has traditionally been the cornerstone of anatomy education. However, in recent decades, its role has come under increasing scrutiny. Comprehensive historical analyses explaining this shift remain limited. This chronologically structured review traces the evolution of anatomy teaching from its origins with Herophilus in the 3rd century BC to the advent of contemporary digital and artificial intelligence (AI)-enhanced approaches. Key milestones include the 1910 Flexner Report, which emphasized integrated biomedical sciences, widespread curricular reforms, increased reliance on prosection, the rise of minimally invasive surgery, and the incorporation of cadaveric simulation in postgraduate training. Advances in imaging technologies such as computed tomography (CT) and magnetic resonance imaging (MRI), alongside innovations in three-dimensional (3D) printing, digital dissection platforms, and virtual or augmented reality (VR/AR), have significantly reshaped anatomy instruction. Internet-based learning and mobile technologies have further transformed self-directed study through accessible, interactive resources. Most recently, AI has introduced capabilities such as personalized tutoring, performance prediction, automated assessment, and intraoperative anatomical guidance. This review highlights the value of a blended approach that integrates cadaveric experience with technological innovations. Future curricula should prioritize optimizing the sequence and combination of these modalities while ensuring equitable access and preparing students for real-world clinical challenges.
Quality assessment of ultra low dose-low dose orthopantomograms reconstructed from CBCT for orthodontic purposes
(2025-01-01) van Bunningen R.H.; Dijkstra P.U.; Dieters A.J.A.; van der Stelt P.; van der Meer W.J.; Kuijpers-Jagtman A.M.; van Bunningen R.H.; Mahidol University
Introduction: This study aimed to analyze the image quality of standard dose orthopantomograms (sd-PAN), extracted PAN from standard dose cone-beam computed tomography (CBCT [extr-PAN]), and from reduced-dose ultra low dose-low dose CBCT (rd-PAN). Methods: Image pairs, sd-CBCT and sd-PAN, of patients were selected if taken within 6 months of each other. From the sd-CBCT, an extr-PAN was extracted, and a simulated rd-PAN (sim rd-PAN) was constructed using a filtering technique. Three experienced orthodontists assessed image quality by means of 9 yes-and-no statements. For subjective statements (1-5), observers’ opinions of technical acceptability and visibility of anatomic structures, observers indicated their disagreement or agreement. For objective statements (6-9), regarding comparability to a gold standard, observers indicated the presence of dental structures. Positive response rates were calculated for the subjective statements. Agreement rates with the gold standard were calculated for the objective statements. Thresholds for acceptable image quality were if ≥2 observers agreeing with the subjective statements or agreeing with the gold standard (objective statements) for 90% for sd-PANs and 85% for both extr-PANs and sim rd-PANs. Results: In total, images of 43 patients were included. For the subjective statements, only the sd-PAN met the threshold for technical adequacy (95.3%) and suitability for orthodontic treatment planning (95.3%). For objective statements 6, 7, and 9, extr-PAN and sim rd-PAN images met the threshold for acceptable quality, whereas the sd-PAN met the threshold for statements 6 and 9. Differences in agreement with the gold standard among images were small (85.7%-87.8%). Conclusions: Sd-PAN images demonstrated superior image quality. Although extr-PAN and sim rd-PAN showed reduced diagnostic image quality for orthodontic diagnosis, differences among the 3 types of PAN regarding the gold standard were small.
Factors Influencing Cultural Tourism Decisions in Ubon Ratchathani
(2025-11-25) Chanwanaku S.; Chanwanaku S.; Mahidol University
This research aims to examine the factors influencing Thai tourists' cultural tourism decisions in Ubon Ratchathani and to propose guidelines for developing these factors. The study employs a quantitative research method, focusing on Thai tourists visiting Ubon Ratchathani for cultural tourism. The sample consisted of 400 respondents, and data were collected via questionnaires using convenience sampling, a nonprobability sampling technique. The data analysis employed descriptive statistics, including frequencies, percentages, and standard deviations, as well as stepwise multiple regression. The findings reveal that four main factors significantly influence cultural tourism decisions at the 0.05 level of significance: accommodation, accessibility, political stability, and cultural activities. Together, these variables can predict cultural tourism decisions with an accuracy of 76.40%. Among them, accommodation, accessibility, and political stability emerge as the most influential. The results indicate that both the government and private sectors, in collaboration with local communities, should prioritize the development of cultural tourism in Ubon Ratchathani. In particular, accessibility can be improved through reliable, safe transportation systems, such as shuttle bus services linking major cultural sites. Political stability must be maintained to enhance tourists’ confidence regarding safety and security. Additionally, cultural activities should be diversified and designed to appeal to tourists of all ages and backgrounds, fostering participation, interaction, and memorable experiences. Overall, the study highlights the importance of infrastructure readiness, political stability, and community engagement in promoting cultural tourism in secondary provinces. These elements are essential for building tourist confidence and ensuring economic, social, and cultural sustainability. Furthermore, the findings help bridge knowledge gaps in understanding tourist decision-making in secondary destinations and provide practical guidelines for promoting sustainable cultural tourism in Thailand.
XAI-ACSM: An Ensemble-Based Explainable Artificial Intelligence Framework for the Accurate Prediction of Anticancer Small Molecules
(2025-12-02) Schaduangrat N.; Mookdarsanit P.; Mahmud S.M.H.; Kusonmano K.; Mookdarsanit L.; Shoombuatong W.; Schaduangrat N.; Mahidol University
Cancer continues to be a leading cause of mortality worldwide. While conventional therapies such as chemotherapy, radiation, and immunotherapy remain mainstays in clinical oncology, these approaches often result in systemic toxicity, adverse side effects, and the emergence of drug resistance. Small-molecule drugs have gained prominence as potent anticancer agents due to their favorable drug-like profiles, enabling oral bioavailability and systemic efficacy. The incorporation of computational methodologies has further revolutionized anticancer drug discovery. In particular, machine learning (ML) techniques have shown considerable success in accelerating the identification and optimization of small-molecule candidates. Therefore, we propose a novel ensemble-based explainable artificial intelligence (XAI) framework, termed XAI-ACSM, for the identification and characterization of anticancer small molecules (ACSMs) using only SMILES notation. XAI-ACSM was initially developed through a comprehensive evaluation of five popular ML algorithms in conjunction with 14 molecular descriptors derived from five different feature encoding schemes. Then, these molecular descriptors and ML algorithms were employed to develop 70 baseline models. Finally, the most effective baseline models were selected and integrated to provide high-precision prediction outcomes using a probability averaging strategy. Both cross-validation and independent tests showed that XAI-ACSM outperformed its baseline models and the existing method. Remarkably, XAI-ACSM achieved an accuracy of 0.826, specificity of 0.926, and MCC of 0.666 over the independent test data set, which were 3.65, 9.60, and 8.63% higher than the existing method. Furthermore, XAI-ACSM was applied to identify potential ACSMs among FDA-approved drugs, with predictions validated through molecular docking against the most prevalent cancer targets. XAI-ACSM offers a practical approach for screening large chemical libraries to identify potential ACSMs, particularly among compounds with limited existing characterization, while helping to reduce time and resource requirements.
One Health Implementation Cycle, Stakeholder Analysis and Engagement
(2024-01-01) Rüegg S.R.; Traore T.; Pettan-Brewer C.; Figueroa D.; Becerra N.C.; Ormea V.; Ratanakorn P.; Plangsangmas T.; Queenan K.; Häsler B.; Maassen C.B.M.; Thys S.; Rüegg S.R.; Mahidol University
The chapter introduces the One Health implementation cycle with all steps that occur during the implementation of a project or policy. We start with an introduction to the implementation of activities in socio-ecological systems (SES), which are, by definition, complex and dynamic. We then explore the kind of challenges we encounter in SES and how these determine the importance of engaging stakeholders in the problem statement, in the understanding of the SES itself and in the co-production of solutions. The cycle starts with stating the problem in an inclusive way and exploring the stakeholders systematically, to leave no one behind. Then, we start a community of practice by co-producing a common understanding of the SES and the challenge. We then reach out and will discover what conflicting perspectives and interests we may encounter and how to deal with them to align behind a common theory of change. This forms the basis for other parts in the implementation cycle, which are covered in Chapters 11, 12 and 13.