Journals / Yönetim ve Ekonomi Dergisi / 2026 / Cilt: 33 Sayı: 2

Ultrasound Device Selection in Health Institutions: An Analysis with Fuzzy DEMATEL and Fuzzy MULTIMOORA Methods

Sağlık Kurumlarında Ultrason Cihazı Seçimi: Bulanık DEMATEL ve Bulanık MULTIMOORA Yöntemleri ile Analizi

Alkan Durmuş(DOKUZ EYLÜL ÜNİVERSİTESİ)0000-0002-5806-9962
Pages
251–288
Publication Date
2026-06-18
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicated that "Screen and Visual Features," "Reliability and Quality Standards," "User-Friendly Interface," and "Compatibility & Integration" were the most critical factors.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to optimize the selection process of ultrasound devices in healthcare institutions through a systematic and scientific approach by employing Fuzzy DEMATEL and Fuzzy MULTIMOORA methods.
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Key Findings & Data:Since ultrasound devices play a critical role in diagnostic and therapeutic procedures, their selection must be based on a comprehensive evaluation of technical, clinical, and economic criteria.
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Conclusion & Impact:The results indicated that "Screen and Visual Features," "Reliability and Quality Standards," "User-Friendly Interface," and "Compatibility & Integration" were the most critical factors.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Ultrason cihazı seçimi · Bulanık DEMATEL · Bulanık MULTIMOORA

Abstract

This study aims to optimize the selection process of ultrasound devices in healthcare institutions through a systematic and scientific approach by employing Fuzzy DEMATEL and Fuzzy MULTIMOORA methods. Since ultrasound devices play a critical role in diagnostic and therapeutic procedures, their selection must be based on a comprehensive evaluation of technical, clinical, and economic criteria. Traditional decision-making methods often fail to adequately address the interdependencies among criteria, making fuzzy logic-based multi-criteria decision-making (MCDM) methods highly beneficial for such complex selection processes. Initially, the Fuzzy DEMATEL method was applied to identify the most influential criteria in ultrasound device selection and to analyze the causal relationships among these criteria. The results indicated that "Screen and Visual Features," "Reliability and Quality Standards," "User-Friendly Interface," and "Compatibility & Integration" were the most critical factors. Subsequently, the Fuzzy MULTIMOORA method was utilized to rank alternative devices based on three different approaches: Ratio System, Full Multiplicative Form, and Reference Point Approach. The integration of these methods provided a robust decision-making framework for selecting the most suitable ultrasound device. The findings underscore the significance and reliability of using multi-criteria decision-making methods in ultrasound device selection. The final evaluation determined that the most appropriate ultrasound device exhibited superior image quality, a user-friendly design, and high technical reliability. This study contributes to healthcare decision-making by offering a structured decision support model, facilitating more informed and effective procurement processes for medical devices. Key Words: Ultrasound device selection, Fuzzy DEMATEL, Fuzzy MULTIMOORA, Multi-Criteria Decision Making (MCDM) JEL Classification: I18, C44, D81

Özet

Bu çalışma, sağlık kurumlarında ultrason cihazı seçim sürecini sistematik ve bilimsel bir yaklaşımla ele almak amacıyla Bulanık DEMATEL ve Bulanık MULTIMOORA yöntemlerini kullanarak kapsamlı bir analiz gerçekleştirmiştir. Ultrason cihazları, sağlık hizmetlerinde teşhis ve tedavi süreçlerinde kritik bir rol oynadığından, cihaz seçimi yapılırken teknik, klinik ve ekonomik kriterlerin çok yönlü olarak değerlendirilmesi gerekmektedir. Geleneksel karar verme yöntemleri, kriterler arasındaki etkileşimleri yeterince ele alamadığı için bulanık mantık tabanlı çok kriterli karar verme (ÇKKV) yöntemleri bu tür seçim süreçlerinde önemli avantajlar sunmaktadır. Öncelikle, Bulanık DEMATEL yöntemi kullanılarak, ultrason cihazı seçiminde en etkili kriterlerin belirlenmesi ve kriterler arası neden-sonuç ilişkilerinin analizi yapılmıştır. Elde edilen sonuçlara göre, “Ekran ve Görsel Özellikler”, “Güvenilirlik ve Kalite Standartları”, “Kullanıcı Dostu Arayüz” ve “Uyumluluk & Entegrasyon” kriterleri en yüksek etkiye sahip faktörler olarak belirlenmiştir. Daha sonra, Bulanık MULTIMOORA yöntemi uygulanarak alternatif cihazlar Oran Yöntemi, Tam Çarpımsal Yöntem ve Referans Noktası Yaklaşımı ile sıralanmış ve en uygun cihaz belirlenmiştir. Elde edilen bulgular, ultrason cihazı seçiminde çok kriterli karar verme yöntemlerinin kullanımının önemini ve güvenilirliğini ortaya koymaktadır. Çalışma sonucunda en uygun cihazın yüksek görüntü kalitesi, kullanıcı dostu tasarım ve teknik güvenilirlik açısından en iyi performansı gösteren cihaz olduğu belirlenmiştir. Bu çalışma, sağlık yöneticileri ve karar vericiler için sistematik bir karar destek modeli sunarak, tıbbi cihaz seçiminde daha bilinçli kararlar alınmasını sağlamaktadır. Anahtar Kelimeler: Ultrason cihazı seçimi, Bulanık DEMATEL, Bulanık MULTIMOORA, Çok Kriterli Karar Verme

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Cite This Article

Durmuş, A. (2026). Ultrasound Device Selection in Health Institutions: An Analysis with Fuzzy DEMATEL and Fuzzy MULTIMOORA Methods. Yönetim ve Ekonomi Dergisi, Cilt: 33 Sayı: 2, 251–288. https://doi.org/10.18657/yonveek.1657789

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References (105)

  1. Abdel-Basset, M., Manogaran, G., Gamal, A., & Smarandache, F. (2019). A group decision making framework based on neutrosophic TOPSIS approach for smart medical device selection. Journal of medical systems, 43, 1-13.
  2. Adunlin, G., Diaby, V., & Xiao, H. (2015). Application of multicriteria decision analysis in health care: a systematic review and bibliometric analysis. Health Expectations, 18(6), 1894-1905.
  3. Ağaç, G., & Baki, B. (2016). Sağlık alanında çok kriterli karar verme teknikleri kullanımı: Literatür incelemesi. Hacettepe Sağlık İdaresi Dergisi, 19(3).
  4. Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals. International Journal of Medical Informatics, 84, 166–188.
  5. Arslan, H. M. Determination of the Most Appropriate Ultrasound Device in Healthcare Institutions with the Critic-GRA Hybrid Method. Medical Records, 5(3), 541-8.
  6. Awasthi, A., & Baležentis, T. (2017). A hybrid approach based on BOCR and fuzzy MULTIMOORA for logistics service provider selection. International Journal of Logistics Systems and Management, 27(3), 261–282.
  7. Aydin, S. (2018). Augmented reality goggles selection by using neutrosophic MULTIMOORA method. Journal of Enterprise Information Management, 31(4), 565–576.
  8. Baran-Kooiker, A., Czech, M., & Kooiker, C. (2018). Multi-criteria decision analysis (MCDA) models in health technology assessment of orphan drugs—a systematic literature review. Next steps in methodology development? Frontiers in public health, 6, 287. Barber, C., Azrael, D., Berrigan, J., Betz, M., Brandspigel, S., Runyan, C., … &
  9. Miller, M. (2023). Selection and use of firearm and medication locking devices in a lethal means counseling intervention. Crisis, 44(3), 216-223. Baykasoğlu, A., V. Kaplanoğlu, Z. D. U. Durmuşoğlu, and C. Şahin. 2013. “Integrating Fuzzy DEMATEL and Fuzzy Hierarchical TOPSIS Methods for Truck Selection.” Expert Systems with Applications, 40: 899–907
  10. Becker, D., Tafoya, C., Becker, S., Kruger, G., Tafoya, M., & Becker, T. (2016). The use of portable ultrasound devices in low‐ and middle‐income countries: a systematic review of the literature. Tropical Medicine & International Health, 21(3), 294-311.
  11. Brauers, W., & Zavadskas, E. K. (2011). MULTIMOORA optimization used to decide on a bank loan to buy property. Technological and Economic Development of Economy, 17(1), 174–188.
  12. Buhumaid, R., Salman, H., & Kilian, P. (2024). From classroom to bedside: the role of point‐of‐care ultrasound in undergraduate medical education. Hong Kong Journal of Emergency Medicine, 31(6), 447-454.
  13. Buonsenso, D. and Rose, C. (2021). Implementation of lung ultrasound in low- to middle-income countries: a new challenge global health?. European Journal of Pediatrics, 181(1), 1-8.
  14. Büyüközkan, G., & Göçer, F. (2019). Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Computing, 23(20), 10085-10103.
  15. Büyüközkan, G., and G. Çiftçi. (2012). “A Novel Hybrid MCDM Approach Based on Fuzzy DEMATEL, Fuzzy ANP and Fuzzy TOPSIS to Evaluate Green Suppliers.” Expert Systems with Applications, 39: 3000–3011
  16. Chakraborty, S., Raut, R. D., Rofin, T. M., & Chakraborty, S. (2023). A comprehensive and systematic review of multi-criteria decision-making methods and applications in healthcare. Healthcare Analytics, 100232.
  17. Chang, B., Chih-Wei Chang, and Chih-Hung Wu. (2011). “Fuzzy DEMATEL Method for Developing Supplier Selection Criteria.” Expert Systems with Applications, 38: 1850–1858
  18. Chatburn, R. L., & Primiano Jr, F. P. (2001). A new system for understanding modes of mechanical ventilation. Respiratory care, 46(6), 604-621.
  19. Chen, Y., Ran, Y., Huang, G., Xiao, L., & Zhang, G. (2021). A new integrated MCDM approach for improving QFD based on DEMATEL and extended MULTIMOORA under uncertainty environment. Applied Soft Computing, 105, 107222.
  20. Denny, S., Minteer, W., Fenning, R., Aggarwal, S., Lee, D., Raja, S., … & Fox, J. (2018). Ultrasound curriculum taught by first-year medical students: a four-year experience in tanzania. World Journal of Emergency Medicine, 9(1), 33.
  21. Didier, E. P., & Helmholz Jr, H. F. (1964). Principles in the selection and use of mechanical ventilators and assisters. Medical Clinics of North America, 48(4), 867-876.
  22. Ding, X., & Zhong, J. (2018). Power battery recycling mode selection using an Extended MULTIMOORA method. Scientific Programming, 2018, 1–14.
  23. Dolan, J. (2010). Multi-criteria clinical decision support. The Patient Patient-Centered Outcomes Research, 3(4), 229-248.
  24. Dorfeshan, Y., Mousavi, S. M., Mohagheghi, V., & Vahdani, B. (2018). Selecting project-critical path by a new interval type-2 fuzzy decision methodology based on MULTIMOORA, MOOSRA and TPOP methods. Computers & Industrial Engineering, 120, 160–178.
  25. Durmuş, A. Hastanelerde Tıbbi Malzeme Depo Yeri Seçimi: Bir Vaka Çalışması. İzmir Sosyal Bilimler Dergisi, 7(1), 1-14.
  26. Durmuş, A., & İskender, A. (2025). Yoğun Bakım Ünitelerinde Mekanik Ventilatör Seçimi: Çok Kriterli Karar Verme Perspektifi. Kent Akademisi, 18(1), 263-292.
  27. Eadie, L., Mulhern, J., Regan, L., Mort, A., Shannon, H., Macaden, A., … & Wilson, P. (2017). Remotely supported prehospital ultrasound: a feasibility study of real-time image transmission and expert guidance to aid diagnosis in remote and rural communities. Journal of Telemedicine and Telecare, 24(9), 616-622.
  28. Elezbawy, B., Fasseeh, A. N., Németh, B., Gamal, M., Eldebeiky, M., Refaat, R.,. & Kalò, Z. (2022). A multicriteria decision analysis (MCDA) tool to purchase implantable medical devices in Egypt. BMC Medical Informatics and Decision Making, 22(1), 289.
  29. Erbay, E., & Akyürek, Ç. E. (2020). Hastanelerde çok kriterli karar verme uygulamalarının sistematik derlemesi, Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Vol. 22, No. 2, pp. 612-645.
  30. F. Zhou, X. Wang, M.K. Lim, Y. He, L. Li, Sustainable recycling partner selection using Fuzzy DEMATELAEW-FVIKOR: A case study in small-and-medium enterprises (SMEs), Journal of Cleaner Production, 196, 489-504, 2018.
  31. Fattahi, R., & Khalilzadeh, M. (2018). Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety Science, 102, 290–300.
  32. Gençol, K. and Güngör, M. (2023). Enhancing the quality of compressed breast ultrasound imagery through application of wavelet convolutional neural networks. Traitement Du Signal, 40(5), 2139-2146.
  33. Glaize, A., Duenas, A., Martinelly, C., & Fagnot, I. (2019). Healthcare decision‐making applications using multicriteria decision analysis: a scoping review. Journal of Multi-Criteria Decision Analysis, 26(1-2), 62-83.
  34. Goulart, T., Cruz, R., & Carvalho, E. (2023). Central retinal artery occlusion diagnosed by color doppler ultrasonography: a case report. International Journal of Health Science, 3(33), 2-6.
  35. Grace, K. (1998). THE VENTILATOR: Selection of Mechanical Ventilators. Critical care clinics, 14(4), 563-580.
  36. H. Li, W. Wang, L. Fan, Q. Li, X. Chen, (2020). A novel hybrid MCKV model for machine tool selection using Fuzzy DEMATEL, entropy weighting and later defuzification VIKOR, Applied Soft Computing Journal, 91
  37. Hafezalkotob, A., Hafezalkotob, A., Liao, H., & Herrera, F. (2019). An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges. Information Fusion, 51(December 2018), 145–177.
  38. Hafezalkotob, A., Hami-Dindar, A., Rabie, N., & Hafezalkotob, A. (2018). A decision support system for agricultural machines and equipment selection: A case study on olive harvester machines. Computers and Electronics in Agriculture, 148, 207–216.
  39. Hodgett, R. (2015). Comparison of multi-criteria decision-making methods for equipment selection. The International Journal of Advanced Manufacturing Technology, 85(5-8), 1145-1157.
  40. Houria, Z. B., Masmoudi, M., Hanbali, A. A., Khatrouch, I., & Masmoudi, F. (2016). Quantitative techniques for medical equipment maintenance management. European journal of industrial engineering, 10(6), 703-723.
  41. Improta, G., Converso, G., Murino, T., Gallo, M., Perrone, A., & Romano, M. (2019). Analytic hierarchy process (ahp) in dynamic configuration as a tool for health technology assessment (hta): the case of biosensing optoelectronics in oncology. International Journal of Information Technology & Decision Making, 18(05), 1533-1550.
  42. Ivlev, I., Vacek, J., & Kneppo, P. (2015). Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research, 247(1), 216-228.
  43. Jha, S., Gupta, M., Dev, B., Regmi, S., Chaudhary, A., & Mahato, A. (2020). Significance of ultrasound in diagnosis of various musculoskeletal disorder. Birat Journal of Health Sciences, 5(3), 1161-1165.
  44. Joshi, D., & Kumar, S. (2016). Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. European Journal of Operational Research, 248(1), 183-191.
  45. Jung, E., Dinkel, J., Verloh, N., Brandenstein, M., Stroszczynski, C., Jung, F., … & Rennert, J. (2021). Wireless point-of-care ultrasound: first experiences with a new generation handheld device. Clinical Hemorheology and Microcirculation, 79(3), 463-474.
  46. K.P. Lin, M.L. Tseng, P.F. Pai, Sustainable supply chain management using approximate Fuzzy DEMATEL method, Resources, Conservation and Recycling, 128, 134-142, 2018.
  47. Karaca, C., & Ulutaş, A. (2017). Supplier performance evaluation by using SWARA and MULTIMOORA. In edited by A. M. Çilingirtürk, A. Albrychiewicz-Słocińska, B. B. Bali (Ed.), Economics management & econometrics (pp. 137–151). IJOPEC.
  48. Kaya, G. K. (2021). Rational Decision-Making in Purchasing Medical Devices. Proceedings of the International Conference on Industrial Engineering and Operations Management Rome, Italy, August 2-5, 2021
  49. Keleş, M. K., Özdağoğlu, A., & Eren, F. Y. (2019). Bir laboratuvarda tam kan sayım cihazı alternatiflerinin SWARA, WPM, TODİM VE AHS yöntemleri ile değerlendirilmesi. İzmir İktisat Dergisi, 34(4), 511-526.
  50. Keller, J. P., Comparative evaluations of medical devices, in Clinical Engineering Handbook, Second Edition, Proceedings of the International Conference on Industrial Engineering and Operations Management Rome, Italy, August 2-5, 2021
  51. Khan, I., Pintelon, L., & Martin, H. (2022). The application of multicriteria decision analysis methods in health care: a literature review. Medical Decision Making, 42(2), 262-274.
  52. Laufer, F. N. (1990). Managerial decision-making in the laboratory. Clinical Laboratory Management Review, 4, 425–431.,
  53. Le, M., Voigt, L., Nathanson, R., Maw, A., Johnson, G., Dancel, R., … & Soni, N. (2022). Comparison of four handheld point-of-care ultrasound devices by expert users. The Ultrasound Journal, 14(1).
  54. Lee, Y. C., Chung, P. H., & Shyu, J. Z. (2017). Performance evaluation of medical device manufacturers using a hybrid fuzzy MCDM. Journal of Scientific & Industrial Research, 76, 28–31.
  55. Lenghong, K. and Apiratwarakul, K. (2020). One year of experience in using hand-held ultrasound as a learning tool in ultrasound rotation at the emergency department. Open Access Macedonian Journal of Medical Sciences, 8(E), 674-677.
  56. Lertprapai, S. (2013). Multiple criteria decision making method with applications. In Int. Math. Forum Vol. 8, No. 7, pp. 347-355.
  57. Li, J., Ma, Y., Zhang, T., Shung, K., & Zhu, B. (2022). Recent advancements in ultrasound transducer: from material strategies to biomedical applications. Bme Frontiers.
  58. Liang, W., Zhao, G., & Hong, C. (2019). Selecting the optimal mining method with extended multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) approach. Neural Computing and Applications, 31(10), 5871–5886.
  59. Lin, R.J. (2013). Using fuzzy DEMATEL to evaluate the green supply chain management practices. J. Clean. Prod., 40, 32–39
  60. Liu, H. C., Zhao, H., You, X. Y., & Zhou, W. Y. (2019). Robot evaluation and selection using the hesitant fuzzy linguistic MULTIMOORA method. Journal of Testing and Evaluation, 47(2), 1405–1426.
  61. Liu, H.-C., Yang, M., Zhou, M., & Tian, G. (2018). An integrated multi-criteria decision making approach to location planning of electric vehicle charging stations. IEEE Transactions on Intelligent Transportation Systems, 20(1), 362–373.
  62. Lu, M. T., Lin, S. W., & Tzeng, G. H. (2013). Improving RFID adoption in Taiwan's healthcare industry based on a DEMATEL technique with a hybrid MCDM model. Decision Support Systems, 56, 259–269.
  63. Maita, H., Kobayashi, T., Akimoto, T., Hirano, T., Osawa, H., & Kato, H. (2022). Evaluation of simulation-based ultrasound education using a bladder simulator for medical students in japan: a prospective observational study. Journal of Medical Ultrasonics, 50(1), 73-80.
  64. Mkalaf, K. (2022). Application the risk-based maintenance for optimizing the overall medical devices safety. Journal of Techniques, 4(4), 111-118.
  65. Montevechi, J., Guimaraes, I. F., De Oliveira, M. L. M., & Friend, J. D. (2010). Decision-making with multiple criteria in the selection of ultrasonic scanning system in a private hospital in Brazil. International Journal of the Analytic Hierarchy Process, 2(1).
  66. Naznin, A., Kadir, M., Begum, F., & Rabbani, K. (2024). Comparative performance of low-cost portable scanner in pregnancy profile ultrasonography: a promising adjunct to telemedicine. Global Clinical Engineering Journal, 6(3), 26-36.
  67. Nielsen, M., Søgaard, S., Andersen, S., Skjoldbye, B., Hansen, K., Rafaelsen, S., … & Carlsen, J. (2021). Highlights of the development in ultrasound during the last 70 years: a historical review. Acta Radiologica, 62(11), 1499-1514.
  68. Nobre, F. F., Trotta, L. T. F., & Gomes, L. F. A. M. (1999). Multi-criteria decision making—An approach to setting priorities in health care. Statistics in Medicine, 18, 3345–3354
  69. Ottardi, C., Damonti, A., Porazzi, E., Foglia, E., Ferrario, L., Villa, T.,. & Galbusera, F. (2017). A comparative analysis of a disposable and a reusable pedicle screw instrument kit for lumbar arthrodesis: integrating HTA and MCDA. Health economics review, 7, 1-10.
  70. Özçelik, G., & Nalkıran, M. (2021). An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system. International Journal of Fuzzy Systems, 23(7), 2348-2366.
  71. Özdağoğlu, A., Keleş, M. K., & Eren, F. Y. (2020). SWARA tabanli WSM ve CODAS yöntemleri ile biyokimya hormon cihazi seçimi. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 10(1), 371-396.
  72. Özdağoğlu, A., Keleş, M. K., & Eren, F. Y. (2021). Laboratuvar Kan Gazı Cihazı Alternatiflerinin Bulanık VIKOR ve Bulanık EDAS ile Değerlendirilmesi. Ordu Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Araştırmaları Dergisi, 11(1), 220-237.
  73. P.S. Parmar and T.N. Desai, Evaluating sustainable lean six sigma enablers using Fuzzy DEMATEL: A case of an Indian manufacturing organization, Journal of Cleaner Production, 265, 2020
  74. Park, J., Kim, E., & Shin, K. (2019). Developing an evaluation framework for selecting optimal medical devices. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 64.
  75. Patil, S. K., and R. Kant. 2014. “A Hybrid Approach Based on Fuzzy DEMATEL and FMCDM to Predict Success of Knowledge Management Adoption in Supply Chain.” Applied Soft Computing 18: 126–135 Qiu, Y., Gigliotti, J., Wallace, M., Griggio, F., Démoré, C., Cochran, S., … &
  76. Trolier‐McKinstry, S. (2015). Piezoelectric micromachined ultrasound transducer (pmut) arrays for integrated sensing, actuation and imaging. Sensors, 15(4), 8020-8041.
  77. Ranger, B., Bradburn, E., Chen, Q., Kim, M., Noble, J., & Papageorghiou, A. (2023). Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape. Gates Open Research, 7, 133.
  78. Rempell, J., Saldaña, F., DiSalvo, D., Kumar, N., Stone, M., Chan, W., … & Kohler, M. (2016). Pilot point-of-care ultrasound curriculum at harvard medical school: early experience. Western Journal of Emergency Medicine, 17(6), 734-740.
  79. Rossi, D., Marciano, F., & Cabassa, P. (2019). A multi-criteria methodology for evaluating alternative ultrasound devices. Ergonomics, 62(10), 1301-1312.
  80. Rykkje, A., Carlsen, J., & Nielsen, M. (2019). Hand-held ultrasound devices compared with high-end ultrasound systems: a systematic review. Diagnostics, 9(2), 61.
  81. Sayed, A., Smajlovic, F., & Junuzovic, D. (2011). Application of ultrasound in medicine. Acta Informatica Medica, 19(3), 168.
  82. Sayed, M. and Zaghrini, E. (2013). Prehospital emergency ultrasound: a review of current clinical applications, challenges, and future implications. Emergency Medicine International, 2013, 1-6.
  83. Shah, S., Tohmasi, S., Frisch, E., Anderson, A., Almog, R., Lahham, S., … & Fox, J. (2019). A comparison of simulation versus didactics for teaching ultrasound to swiss medical students. World Journal of Emergency Medicine, 10(3), 169.
  84. Shbool, ‎., Arabeyyat, O., Al‐Bazi, A., & AlAlaween, W. (2021). An integrated multi-criteria decision-making framework for a medical device selection in the healthcare industry. Cogent Engineering, 8(1). Shbool, Mohammad A., Omar S. Arabeyyat, Ammar Al-Bazi, and Wafa’H. AlAlaween. "An integrated multi-criteria decision-making framework for a medical device selection in the healthcare industry." Cogent Engineering 8, no. 1 (2021): 1968741.
  85. Si, S.L.; You, X.Y.; Liu, H.C.; Zhang, P. DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications. Math. Probl. Eng. 2018, 2018, 33.
  86. Sloane, E. B. et al., Using the analytic hierarchy process as a clinical engineering tool to facilitate an iterative, multidisciplinary, microeconomic health technology assessment, Computers and Operations Research, vol. 30, no. 10, pp. 1447–1465, 2003.
  87. Souzangarzadeh, H., Rezvani, M. J., & Jahan, A. (2017). Selection of optimum design for conical segmented aluminum tubes as energy absorbers: Application of MULTIMOORA method. Applied Mathematical Modelling, 51, 546–560
  88. Stević, Ž., Pamučar, D., Vasiljević, M., Stojić, G., & Korica, S. (2017). Novel integrated multi-criteria model for supplier selection: Case study construction company. Symmetry, 9(11), 279.
  89. Tadić, D., Stefanović, M., Aleksić, A. (2014). The Evaluation and Ranking of Medical Device Suppliers by Using Fuzzy Topsis Methodology. Journal of Intelligent & Fuzzy Systems, 27 (4), 2091-2101.
  90. Tian, Z., Wang, J., Wang, J., & Zhang, H. (2017). An improved MULTIMOORA approach for multi-criteria decision-making based on interdependent inputs of simplified neutrosophic linguistic information. Neural Computing and Applications, 28(S1), 585–597.
  91. Tolga, A. C., Parlak, I. B., & Castillo, O. (2020). Finite-interval-valued Type-2 Gaussian fuzzy numbers applied to fuzzy TODIM in a healthcare problem. Engineering Applications of Artificial Intelligence, 87, 103352.
  92. Toscano, M., Szlachetka, K., Whaley, N., & Thornburg, L. (2020). Evaluating sensitivity and specificity of handheld point-of-care ultrasound testing for gynecologic pathology: a pilot study for use in low resource settings. BMC Medical Imaging, 20(1).
  93. Wahlster, P., Goetghebeur, M., Schaller, S., Kriza, C., Kolominsky-Rabas, P., & National Leading-Edge Cluster Medical Technologies ‘Medical Valley EMN’. (2015). Exploring the perspectives and preferences for HTA across German healthcare stakeholders using a multi-criteria assessment of a pulmonary heart sensor as a case study. Health Research Policy and Systems, 13, 1-11.
  94. Wang, C., Zheng, Y., Xiong, C., Sun, L., & Wang, J. (2022). Preliminary exploration of theory and practice training of 5g ultrasonic remote consultation in grassroot hospitals. BMC Health Services Research, 22(1).
  95. Willemsen, K., Nizak, R., Noordmans, H., Castelein, R., Weinans, H., & Kruyt, M. (2019). Challenges in the design and regulatory approval of 3d-printed surgical implants: a two-case series. The Lancet Digital Health, 1(4), e163-e171.
  96. Wu, X., Liao, H., Xu, Z., Hafezalkotob, A., & Herrera, F. (2018). Probabilistic linguistic MULTIMOORA: A multicriteria decision making method based on the probabilistic linguistic expectation function and the improved Borda rule. IEEE Transactions on Fuzzy Systems, 26(6), 3688–3702.
  97. Yaman, Tutku Tuncalı, and Gonca Reyhan Akkartal. 2020. “Warehouse Location Selection Decision Systems for Medical Sector.” Paper presented at the 2020 fourth world Conference on smart trends in systems, security and sustainability (WorldS4).
  98. Yang, M., Gao, J., Jing, W., Bao, Z., Han, D., & Liu, B. (2019). Clinical trial assessment principles of national class iii medical devices in china. Orthopaedic Surgery, 11(5), 715-719.
  99. Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353. Zavadskas, E. K., Bausys, R., Juodagalviene, B., & Garnyte-
  100. Sapranaviciene, I. (2017). Model for residential house element and material selection by neutrosophic MULTIMOORA method. Engineering Applications of Artificial Intelligence, 64, 315–324.
  101. Zhang, Y., Luo, Y., Qiu, L., Lü, Q., & Lu, X. (2023). Remote ultrasound real‐time consultation and quality control system. International Journal of Imaging Systems and Technology, 34(1).
  102. Zhao, H., You, J.-X., & Liu, H.-C. (2017). Failure mode and effect analysis using MULTIMOORA method with continuous weighted entropy under interval-valued intuitionistic fuzzy environment. Soft Computing, 21(18), 5355–5367.
  103. Zhou, Q., W. Huang, and Y. Zhang. 2011. “Identifying Critical Success Factors in Emergency Management Using a Fuzzy DEMATEL Method.” Safety Science 49: 243–252.
  104. Elezbawy, B., Fasseeh, A. N., Németh, B., Gamal, M., Eldebeiky, M., Refaat, R.,. & Kalò, Z. (2022). A multicriteria decision analysis (MCDA) tool to purchase implantable medical devices in Egypt. BMC Medical Informatics and Decision Making, 22(1), 289.
  105. Ottardi, C., Damonti, A., Porazzi, E., Foglia, E., Ferrario, L., Villa, T.,. & Galbusera, F. (2017). A comparative analysis of a disposable and a reusable pedicle screw instrument kit for lumbar arthrodesis: integrating HTA and MCDA. Health economics review, 7, 1-10.