1
|
Puška A, Štilić A, Pamucar D, Simic V, Petrović N. Optimal selection of healthcare waste treatment devices using fuzzy-rough approach. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024:10.1007/s11356-024-32630-5. [PMID: 38430441 DOI: 10.1007/s11356-024-32630-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 02/20/2024] [Indexed: 03/03/2024]
Abstract
The escalating volume of healthcare waste (HCW) generated by healthcare facilities poses a pressing challenge for all nations. Adequate management and disposal of this waste are imperative to mitigate its adverse impact on human lives, wildlife, and the environment. Addressing this issue in Bosnia and Herzegovina involves the establishment of a regional center dedicated to HCW management. In practice, there are various treatments available for HCW management. Therefore, it is necessary to determine the priority for procuring different treatments during the formation of this center. To assess these treatment devices, expert decision-making employed the fuzzy-rough approach. By leveraging extended sustainability criteria, experts initially evaluated the significance of these criteria and subsequently assessed the devices for HCW treatment. Employing the fuzzy-rough LMAW (Logarithm Methodology of Additive Weights), the study determined the importance of criteria, highlighting "Air emissions" and "Annual usage costs" as the most critical factors. Utilizing the fuzzy-rough CoCoSo (the Combined Compromise Solution) method, six devices employing incineration or sterilization for HCW treatment were ranked. The findings indicated that the "Rotary kiln" and "Steam disinfection" emerged as the most favorable devices for HCW treatment based on this research. This conclusion was validated through comparative and sensitivity analyses. This research contributes by proposing a solution to address Bosnia and Herzegovina's HCW challenge through the establishment of a regional center dedicated to HCW management.
Collapse
Affiliation(s)
- Adis Puška
- Department of Public Safety, Government of Brčko District, Brcko District, Bosnia and Herzegovina
| | - Anđelka Štilić
- Academy of Applied Studies Belgrade, College of Tourism, Bulevar Zorana Đinđića 152a, 11070, Belgrade, Serbia
| | - Dragan Pamucar
- Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia.
- College of Engineering, Yuan Ze University, Taoyuan City, Taiwan.
- Department of Computer Science and Mathematics, Lebanese American University, Byblos, Lebanon.
| | - Vladimir Simic
- Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11010, Belgrade, Serbia
- Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, 02841, Republic of Korea
| | - Nataša Petrović
- Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia
| |
Collapse
|
2
|
Rus G, Andras I, Vaida C, Crisan N, Gherman B, Radu C, Tucan P, Iakab S, Hajjar NA, Pisla D. Artificial Intelligence-Based Hazard Detection in Robotic-Assisted Single-Incision Oncologic Surgery. Cancers (Basel) 2023; 15:3387. [PMID: 37444497 DOI: 10.3390/cancers15133387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 06/14/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
THE PROBLEM Single-incision surgery is a complex procedure in which any additional information automatically collected from the operating field can be of significance. While the use of robotic devices has greatly improved surgical outcomes, there are still many unresolved issues. One of the major surgical complications, with higher occurrence in cancer patients, is intraoperative hemorrhages, which if detected early, can be more efficiently controlled. AIM This paper proposes a hazard detection system which incorporates the advantages of both Artificial Intelligence (AI) and Augmented Reality (AR) agents, capable of identifying, in real-time, intraoperative bleedings, which are subsequently displayed on a Hololens 2 device. METHODS The authors explored the different techniques for real-time processing and determined, based on a critical analysis, that YOLOv5 is one of the most promising solutions. An innovative, real-time, bleeding detection system, developed using the YOLOv5 algorithm and the Hololens 2 device, was evaluated on different surgical procedures and tested in multiple configurations to obtain the optimal prediction time and accuracy. RESULTS The detection system was able to identify the bleeding occurrence in multiple surgical procedures with a high rate of accuracy. Once detected, the area of interest was marked with a bounding box and displayed on the Hololens 2 device. During the tests, the system was able to differentiate between bleeding occurrence and intraoperative irrigation; thus, reducing the risk of false-negative and false-positive results. CONCLUSION The current level of AI and AR technologies enables the development of real-time hazard detection systems as efficient assistance tools for surgeons, especially in high-risk interventions.
Collapse
Affiliation(s)
- Gabriela Rus
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| | - Iulia Andras
- Department of Urology, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Calin Vaida
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| | - Nicolae Crisan
- Department of Urology, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Bogdan Gherman
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| | - Corina Radu
- Department of Internal Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Paul Tucan
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| | - Stefan Iakab
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| | - Nadim Al Hajjar
- Department of Urology, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
- Department of Surgery, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania
| | - Doina Pisla
- Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
| |
Collapse
|
3
|
Zafaranlouei N, Ghoushchi SJ, Haseli G. Assessment of sustainable waste management alternatives using the extensions of the base criterion method and combined compromise solution based on the fuzzy Z-numbers. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:62121-62136. [PMID: 36935442 PMCID: PMC10025064 DOI: 10.1007/s11356-023-26380-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 03/07/2023] [Indexed: 05/10/2023]
Abstract
A number of factors have contributed to the increase in waste production and diversity of waste, such as the increase in population, alterations in consumption patterns, economic development, income changes, urbanization, and industrialization. The production of different types of waste, such as electronic, urban, hospital, and industrial waste, makes it necessary to classify waste accurately and recognize effective criteria for waste management. To design and operate waste management systems, it is necessary to understand the sources and types of waste, as well as information about their composition and rate of production. As a result, this study aims to rank 21 types of waste according to Iran's economic, social, and environmental criteria, as well as 13 sub-criteria related to those criteria. For this aim, proposed a novel decision-making approach based on the extension of the base criterion method (BCM) and combined compromise solution (CoCoSo) methods under fuzzy Z-numbers. Additionally, sensitivity analysis and comprehensive analysis are conducted on the results of the criteria and alternatives of sustainable waste management. Based on the results of this study, direct profit and reduced landfill are the most important criteria for assessing sustainable waste management alternatives. According to the results of this study, the sub-alternative of industrial metal waste is the most important waste management option. Examining the next sub-alternative ranks under sustainable waste management options (mobile, communication equipment, and battery) shows that electronic waste requires more attention for recycling and sustainable waste management.
Collapse
Affiliation(s)
| | | | - Gholamreza Haseli
- Tecnologico de Monterrey, Escuela de Ingeniería Y Ciencias, Puebla, Mexico
| |
Collapse
|
4
|
Chew X, Khaw KW, Alnoor A, Ferasso M, Al Halbusi H, Muhsen YR. Circular economy of medical waste: novel intelligent medical waste management framework based on extension linear Diophantine fuzzy FDOSM and neural network approach. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:60473-60499. [PMID: 37036648 PMCID: PMC10088637 DOI: 10.1007/s11356-023-26677-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 03/23/2023] [Indexed: 04/11/2023]
Abstract
Environmental pollution has been a major concern for researchers and policymakers. A number of studies have been conducted to enquire the causes of environmental pollution which suggested numerous policies and techniques as remedial measures. One such major source of environmental pollution, as reported by previous studies, has been the garbage resulting from disposed hospital wastes. The recent outbreak of the COVID-19 pandemic has resulted into mass generation of medical waste which seems to have further deteriorated the issue of environmental pollution. This necessitates active attention from both the researchers and policymakers for effective management of medical waste to prevent the harm to environment and human health. The issue of medical waste management is more important for countries lacking sophisticated medical infrastructure. Accordingly, the purpose of this study is to propose a novel application for identification and classification of 10 hospitals in Iraq which generated more medical waste during the COVID-19 pandemic than others in order to address the issue more effectively. We used the Multi-Criteria Decision Making (MCDM) method to this end. We integrated MCDM with other techniques including the Analytic Hierarchy Process (AHP), linear Diophantine fuzzy set decision by opinion score method (LDFN-FDOSM), and Artificial Neural Network (ANN) analysis to generate more robust results. We classified medical waste into five categories, i.e., general waste, sharp waste, pharmaceutical waste, infectious waste, and pathological waste. We consulted 313 experts to help in identifying the best and the worst medical waste management technique within the perspectives of circular economy using the neural network approach. The findings revealed that incineration technique, microwave technique, pyrolysis technique, autoclave chemical technique, vaporized hydrogen peroxide, dry heat, ozone, and ultraviolet light were the most effective methods to dispose of medical waste during the pandemic. Additionally, ozone was identified as the most suitable technique among all to serve the purpose of circular economy of medical waste. We conclude by discussing the practical implications to guide governments and policy makers to benefit from the circular economy of medical waste to turn pollutant hospitals into sustainable ones.
Collapse
Affiliation(s)
- XinYing Chew
- School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia
| | - Khai Wah Khaw
- School of Management, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia
| | - Alhamzah Alnoor
- Management Technical College, Southern Technical University, Basrah, Iraq.
| | - Marcos Ferasso
- Economics and Business Sciences Department, Universidade Autónoma de Lisboa, 1169-023, Lisbon, Portugal
| | - Hussam Al Halbusi
- Department of Management, Ahmed Bin Mohammad Military College, Doha, Qatar
| | - Yousif Raad Muhsen
- Faculty of Engineering, Universiti Putra Malaysia, Seri Kembangan, Selangor, Malaysia
| |
Collapse
|
5
|
Jafarzadeh Ghoushchi S, Bonab SR, Ghiaci AM. A decision-making framework for COVID-19 infodemic management strategies evaluation in spherical fuzzy environment. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2023; 37:1635-1648. [PMID: 36714449 PMCID: PMC9857902 DOI: 10.1007/s00477-022-02355-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 06/18/2023]
Abstract
100 years after the Spanish flu, the COVID-19 crisis showed that large-scale epidemics and pandemics do not belong to the past. On the report of the World Health Organization, COVID-19 is the most significant public health problem of the twenty-first century. Like previous epidemics, the current crisis is accompanied by uncertainty, mistrust, doubt and fear, and this has led to an infodemic connection to the epidemic. So not only are we fighting an epidemic, but also, we are brawling an infodemic. To reduce the social and economic consequences and harmful effects of infodemic health, and to overcome it, we need to implement strategies against infodemic. Evaluating strategies based on multiple characteristics can be considered multi-criteria decision-making (MCDM) problem. According to the literature, there is no study that aims on proposing an integrated approach to evaluate infodemic management strategies under uncertain environment. Therefore, in this paper, an integrated framework based on the extended version of best-worst method (BWM) and Combined Compromise Solution (CoCoSo) methods under a spherical fuzzy set (SFS) is developed for the first time to address the COVID-19 infodemic management strategies selection. Initially, the criteria are weighted using the developed SFS BWM which reduces uncertainty in pairwise comparisons. In the next step, the 15 selected strategies are analyzed and ranked using SFS CoCoSo. The outputs of this paper illustrate that online tools for fact checking COVID-19 information and engage and empower communities are placed in the first and second priorities, respectively. The comparison of ranking results SFS-CoCoSo with other MCDM methods demonstrates the performance of the proposed approach and its ranking stability.
Collapse
|
6
|
Ranjbarzadeh R, Dorosti S, Jafarzadeh Ghoushchi S, Caputo A, Tirkolaee EB, Ali SS, Arshadi Z, Bendechache M. Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods. Comput Biol Med 2023; 152:106443. [PMID: 36563539 DOI: 10.1016/j.compbiomed.2022.106443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/24/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022]
Abstract
The Global Cancer Statistics 2020 reported breast cancer (BC) as the most common diagnosis of cancer type. Therefore, early detection of such type of cancer would reduce the risk of death from it. Breast imaging techniques are one of the most frequently used techniques to detect the position of cancerous cells or suspicious lesions. Computer-aided diagnosis (CAD) is a particular generation of computer systems that assist experts in detecting medical image abnormalities. In the last decades, CAD has applied deep learning (DL) and machine learning approaches to perform complex medical tasks in the computer vision area and improve the ability to make decisions for doctors and radiologists. The most popular and widely used technique of image processing in CAD systems is segmentation which consists of extracting the region of interest (ROI) through various techniques. This research provides a detailed description of the main categories of segmentation procedures which are classified into three classes: supervised, unsupervised, and DL. The main aim of this work is to provide an overview of each of these techniques and discuss their pros and cons. This will help researchers better understand these techniques and assist them in choosing the appropriate method for a given use case.
Collapse
Affiliation(s)
- Ramin Ranjbarzadeh
- School of Computing, Faculty of Engineering and Computing, Dublin City University, Ireland.
| | - Shadi Dorosti
- Department of Industrial Engineering, Urmia University of Technology, Urmia, Iran.
| | | | - Annalina Caputo
- School of Computing, Faculty of Engineering and Computing, Dublin City University, Ireland.
| | | | - Sadia Samar Ali
- Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia.
| | - Zahra Arshadi
- Faculty of Electronics, Telecommunications and Physics Engineering, Polytechnic University, Turin, Italy.
| | - Malika Bendechache
- Lero & ADAPT Research Centres, School of Computer Science, University of Galway, Ireland.
| |
Collapse
|
7
|
Jafarzadeh Ghoushchi S, Shaffiee Haghshenas S, Memarpour Ghiaci A, Guido G, Vitale A. Road safety assessment and risks prioritization using an integrated SWARA and MARCOS approach under spherical fuzzy environment. Neural Comput Appl 2023; 35:4549-4567. [PMID: 36311168 PMCID: PMC9595097 DOI: 10.1007/s00521-022-07929-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 10/03/2022] [Indexed: 02/01/2023]
Abstract
There are a lot of elements that make road safety assessment situations unpredictable and hard to understand. This could put people's lives in danger, hurt the mental health of a society, and cause permanent financial and human losses. Due to the ambiguity and uncertainty of the risk assessment process, a multi-criteria decision-making technique for dealing with complex systems that involves choosing one of many options is an important strategy of assessing road safety. In this study, an integrated stepwise weight assessment ratio analysis (SWARA) with measurement of alternatives and ranking according to compromise solution (MARCOS) approach under a spherical fuzzy (SF) set was considered. Then, the proposed methodology was applied to develop the approach of failure mode and effect analysis (FMEA) for rural roads in Cosenza, southern Italy. Also, the results of modified FMEA by SF-SWARA-MARCOS were compared with the results of conventional FMEA. The risk score results demonstrated that the source of risk (human) plays a significant role in crashes compared to other sources of risk. The two risks, including landslides and floods, had the lowest values among the factors affecting rural road safety in Calabria, respectively. The correlation between scenario outcomes and main ranking orders in weight values was also investigated. This study was done in line with the goals of sustainable development and the goal of sustainable mobility, which was to find risks and lower the number of accidents on the road. As a result, it is thus essential to reconsider laws and measures necessary to reduce human risks on the regional road network of Calabria to improve road safety.
Collapse
Affiliation(s)
| | | | | | - Giuseppe Guido
- Department of Civil Engineering, University of Calabria, Via Bucci, 87036 Rende, Italy
| | - Alessandro Vitale
- Department of Civil Engineering, University of Calabria, Via Bucci, 87036 Rende, Italy
| |
Collapse
|
8
|
Tirkolaee EB, Goli A, Mirjalili S. Circular economy application in designing sustainable medical waste management systems. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:79667-79668. [PMID: 35578082 PMCID: PMC9110080 DOI: 10.1007/s11356-022-20740-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Affiliation(s)
| | - Alireza Goli
- Department of Industrial Engineering and Future Studies Faculty of Engineering, University of Isfahan, Isfahan, Iran
| | - Seyedali Mirjalili
- Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Fortitude Valley, Brisbane, 4006 QLD Australia
- Yonsei Frontier Lab, Yonsei University, Seoul, Republic of Korea
| |
Collapse
|