Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling
Abstract
:1. Introduction
1.1. Background and Significance
1.2. Key Contributions and Novelty
2. Risk Management and Resiliency
- Risk identification: This stage involves discovering all relevant risks that can influence the operations within an enterprise (or system) [66]. These risks might stem from internal and external sources relative to the boundaries of the enterprise [67]. Internal sources generally include production delays, equipment breakdown, or accidents, while external sources mainly include pandemics, cyber-attacks, natural disasters, production or quality problems at the suppliers’ plants, or transportation accidents [68].
- Risk assessment: Supply chain risks are commonly characterized by the probability of their occurrence and the severity of their impact. This stage of the process involves assessing these factors for the identified risks from the risk identification stage [66]. Additionally, in this stage, the risks are ranked based on the enterprise’s risk threshold or tolerance [68].
- Risk management: In this stage, strategies for the probability or severity of the identified supply chain risks are determined. This encompasses options such as risk acceptance (i.e., taking no action to mitigate the risk) and devising approaches for risk avoidance, transfer, or mitigation [69].
3. Materials and Methods
3.1. Causal Model
3.2. System Dynamics Model
AScaling Factor ×[(data management capability level) ×
(1 − diagnosis variability level) ×
(simplicity of app interface level)×
(skin lesion screening viability process level) ×
(level of user contentment) × (1 − delay)]
+δOffset
4. Results
4.1. Baseline Case
4.2. Case #1
4.3. Case #2
4.4. Case #3
4.5. Case #4
4.6. Case #5
4.7. Case #6
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Factor | Description | Capability | Vulnerability |
---|---|---|---|
Resiliency | The ability of the network to provide and maintain an acceptable level of service, and in some cases, to adapt and grow in the face of various faults and challenges, to normal operation [85] | ✓ | |
Health Fulfillment | This refers to the well-being status | ||
Population with Skin Problems | Percentage of people that have skin problems | ||
Determinants of Skin Lesion Development | This factor includes environmental, geographical, climate, and demographics attributes that influence the development of skin lesions | ✓ | |
Actual Necessity Level | Rate of need | ✓ | |
Necessity Level | This refers to demand | ✓ | |
App Affordability | Affordability level of the app in terms of cost and best value | ✓ | |
App Consistency | App consistency level across various smartphone vendors | ✓ | |
Accessibility | This refers to convenience of accessing the tool when needed | ✓ | |
Equitability | This refers to the capability of each individual in need having same likelihood of being served | ✓ | |
User Complaint | This represents the severity and/or number of complaints from users | ✓ | |
User Contentment | This factor refers to the measure of user’s experience/reaction to received services and confidence in the app [25] | ✓ | |
Skin Lesion Screening Viability Process | This refers to the feasibility (viability) of the skin screening method or process (including dermatoscope, smartphone, biopsy, etc.) | ✓ | |
Simplicity of App Interface | This refers to the app’s user friendliness level | ✓ | |
Adaptability | The interface should be flexible and adaptable to different user contexts and devices, ensuring usability across various platforms and screen sizes | ✓ | |
Interactivity | This refers to the app’s ability in providing interactive user experience | ✓ | |
Equipment Malfunction | This factor represents error or faults in the device | ✓ | |
Diagnosis Variability | This refers to variance in diagnoses from one method to another | ✓ | |
Data Management Capability | This refers to the app’s capability in terms of managing and updating data and, in general, the software | ✓ | |
Realtime Data Sharing | App’s ability to collect, update, and transfer information instantly | ✓ | |
Security Breach | This factor consists of attributes compromising security, privacy, and confidentiality such and unauthorized activity | ✓ | |
App Functionality | This is the top level technological factor referring to the app performance | ✓ | |
Skin Lesion Algorithm and Software Management Competitiveness | This implies the level of the app’s skin lesion analysis algorithm competitiveness among the state-of-art techniques | ✓ | |
Image Resolution | This refers to the quality of image acquired for skin lesion analysis | ✓ | |
Power Supply | This represents the battery level of the smart (hand-held) device | ✓ | |
Skin Lesion Screening App Capability | This refers to the app’s capability in terms of including important skin lesion analyses features and functionalities | ✓ | |
Software Malfunction | This refers to software and algorithmic errors | ✓ | |
Delay | This represents the delay of app response in terms of time | ✓ |
Factor | Simplicity | Skin | Skin Lesion | Skin Lesion | Diagnosis | Rate | All the |
---|---|---|---|---|---|---|---|
of App | Lesion App | Algorithm and Software | Screening | Variability | of | Other | |
Interface | Capability | Management | Viability Process | Level | Necessity | Input | |
Case | Level | Level | Competitiveness Level | Level | Variables | ||
Baseline | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Case #1 | 0.5 | 0.5 | 0.9 | 0.5 | 0.5 | 0.5 | 0.5 |
Case #2 | 0.5 | 0.3 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 |
Case #3 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.2 | 0.5 |
Case #4 | 0.8 | 0.8 | 0.8 | 0.8 | 0.2 | 0.5 | 0.5 |
Case #5 | 0.3 | 0.4 | 0.7 | 0.9 | 0.5 | 0.5 | 0.5 |
Case #6 | 0.4 | 0.4 | 0.4 | 0.4 | 0.5 | 0.5 | 0.5 |
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Faezipour, M.; Faezipour, M.; Pourreza, S. Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling. Sustainability 2023, 15, 13832. https://doi.org/10.3390/su151813832
Faezipour M, Faezipour M, Pourreza S. Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling. Sustainability. 2023; 15(18):13832. https://doi.org/10.3390/su151813832
Chicago/Turabian StyleFaezipour, Misagh, Miad Faezipour, and Saba Pourreza. 2023. "Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling" Sustainability 15, no. 18: 13832. https://doi.org/10.3390/su151813832