Interpretability of machine learning-based prediction models in healthcare

Cited by (416)

Items 301–400 of 416

1. Local Surrogate Models With Residual Fuzzy Rules for Model-Agnostic Explanations
   Keyu Wu, Xingchen Hu, Linying Liu, Xiubin Zhu, Jincai Huang, Witold Pedrycz · 2026 · IEEE Transactions on Cybernetics
2. Container-level proof-of-concept monitoring of postharvest apple blue mold using a whole-cell biosensor array and interpretable machine learning
   Yatong Zhu, Mumin Zheng, Yue Guan · 2026 · Food Control
3. The crucial role of machine learning models in predicting current childhood asthma: model comparison, calibration, and SHAP-based interpretation
   Aditya Chakraborty, A. K. M. Raquibul Bashar · 2026 · Frontiers in Public Health
4. Le phénotypage digital pour une pratique clinique en santé mentale mieux informée
   Alan Bougeard, Rose Guay Hottin, Valérie Houde, Thierry Jean, Thibault Piront, Stéphane Potvin, Paquito Bernard, Valérie Tourjman, Luigi De Benedictis, Pierre Orban · 2021 · Santé mentale au Québec
5. Machine Learning for Alzheimer’s Disease Detection Based on Neuroimaging techniques: A Review
   Maha Gharaibeh, Mwaffaq Elhies, Mothanna H. Almahmoud, Sayel M. Abualigah, Omar N. Elayan · 2022 · International Conference on Information and Communication Systems (ICICS)
6. Disjunctive Rule Lists
   Ronilo Ragodos, Tong Wang · 2022 · INFORMS journal on computing
7. Future Directions of Artificial Intelligence and Machine Learning in Healthcare: A Systematic Analysis and Mapping Study
   Hari Mohan Mishra, Bilal Ahmed, Mirza Shuja, Ahmed Qtaishat, Mukesh Kumar · 2023 · International Conference on Information Systems and Computer Networks (ISCON)
8. Using heterogeneous sources of data and interpretability of prediction models to explain the characteristics of careless respondents in survey data
   Leon Kopitar, Gregor Štiglic · 2023 · Scientific Reports
9. Decision Support System Improving the Interpretability of Generated Tree-Based Models
   Diana Klimonová, Viera Anderková, František Babič · 2022 · Acta Electrotechnica et Informatica
10. Development of an Interpretable Model for Improving Differential Diagnosis in Subjects with a Left Ventricular Ejection Fraction Ranging from 40 to 55%
    Katerina Iscra, Miloš Ajčević, Aleksandar Miladinović, Laura Munaretto, Jacopo Giulio Rizzi, Marco Merlo, Accardo Agostino · 2024 · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany
11. Early Prediction of Ductal Carcinoma Histological Subtypes Via Ensemble Transformer Pipelines in Digital Pathology
    Vrishank Chandrasekhar · 2023 · International Conference on Information Communication and Signal Processing (ICICSP)
12. A Novel Security Model for Healthcare Prediction by Using DL
    Anshita Dhoot, Rahul Deva, Varun Shukla · 2024 · Lecture notes in networks and systems
13. Understanding Interpretability in Modeling Biotechnological Processes: A Critical Review
    Estefanía Aguirre-Zapata, Hernán Álvarez, Laura Lema-Pérez, Fernando A di Sciascio, Adriana Amicarelli · 2023 · Workshop on Information Processing and Control
14. Artificial Intelligence and Machine Learning Model for Healthcare
    Harsh K. Trivedi, Sandeep Prabhu, Prathamesh Prabhu · 2023 · IEEE Technology & Engineering Management Conference - Asia Pacific (TEMSCON-ASPAC)
15. Enhancing Medical Insurance Pricing Prediction with SHAP-XGBoost for Informed Decision-Making
    Danh Hong Le · 2024 · Lecture notes in networks and systems
16. Image Captioning for Coronary Artery Disease Diagnosis
    Bruno Magalhães, João Pedrosa, Francesco Renna, Hugo Paredes, Vítor Manuel de Jesus Filipe · 2024 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
17. Risk prediction models for stress urinary incontinence after pelvic organ prolapse (POP) surgery: a systematic review and meta-analysis
    Bi Jun Yu, Hao Chong He, Li Wang, Han Mei Shao, Ying Min Liu, Xiao Ying Yan, Jian Liu · 2025 · BMC Women s Health
18. Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation
    Hugo Porta, Emanuele Dalsasso, Diego Marcos, Devis Tuia · 2025 · IEEE Winter Conference on Applications of Computer Vision
19. Explaining in Diffusion: Explaining a Classifier with Diffusion Semantics
    Tahira Kazimi, Ritika Allada, Pinar Yanardag · 2025 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
20. Enhancing differential diagnosis of IHD and DCM using interpretable machine learning in mildly reduced ejection fraction
    Katerina Iscra, Laura Munaretto, Jacopo Giulio Rizzi, Aleksandar Miladinović, Massimo Zecchin, Luca Dalla Libera, Chiara Baggio, Agostino Accardo, Gianfranco Sinagra, Miloš Ajčević et al. · 2025 · Journal of Cardiovascular Medicine
21. Comprehensive Evaluation of Prototype Neural Networks
    Philipp Schlinge, Steffen Meinert, Martin Atzmueller · 2025 · Künstliche Intell.
22. MoE-Enhanced Explainable Deep Manifold Transformation for Complex Data Embedding and Visualization
    Zelin Zang, Yuhao Wang, Jinlin Wu, Hong Liu, Yue Shen, Zhen Lei, Stan Ziqing Li · 2026 · IEEE Transactions on Pattern Analysis and Machine Intelligence
23. Patient gender identity information in Covid-19 severity detection on 3D chest CT scans via deep learning
    William Olurotimi Falana, Ali Serener, Sertan Serte · 2022 · International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA)
24. How to Reduce the Time Necessary for Evaluation of Tree-Based Models
    Viera Anderková, František Babič · 2022 · Lecture notes in computer science
25. Research on Multimodal Hate Speech Detection Based on Self-Attention Mechanism Feature Fusion
    Junjie Mao, Hanxiao Shi, Xiaojun Li · 2024 · Research Square
26. When Attention Fails: Pitfalls of Attention-Based Model Interpretability for High-Dimensional Clinical Time-Series Modeling
    Shashank Yadav, Vignesh Subbian · 2024 · SSRN Electronic Journal
27. Clinical utility of EHR-based predictive models for identifying high-risk individuals in early cancer detection
    Jiheum Park, Chao Pang, Tristan Y. Lee, Jacob S. Berkowitz, Alexander Z. Wei, Chin Hur, Nicholas P. Tatonetti · 2025 · Research Square
28. Post-Analysis of Predictive Modeling with an Epidemiological Example
    Christina Brester, Ari Voutilainen, Tomi‐Pekka Tuomainen · 2021 · Healthcare
29. Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool
    Chris McWilliams, Eleanor I. Walsh, Avon P. Huxor, Emma L. Turner, Raúl Santos‐Rodríguez · 2021 · medRxiv
30. Interpretable prediction for in-hospital adverse stroke events with feature engineering (Preprint)
    Shuo Zhang, Runzhi Li, Nan Wang, Bo Song, Honghua Dai, Yuming Xu · 2021
31. Data mining with deep learning in biomedical data
    Kuldeep Singh, Jyoteesh Malhotra · 2022 · Elsevier eBooks
32. Foundations
    Ansel Y. Rodríguez‐González, Angel Diaz Pacheco, Ramón Aranda, Miguel Á. Álvarez‐Carmona · 2022 · Wiley eBooks
33. Integrated Artificial Intelligence System with existing system for Predicting the Disease
    S. K. UmaMaheswaran, Anita Gehlot, Bhagwant Singh, Joel Alanya-Beltrán, Nrupura Dixit, Rohit Bansal · 2022 · International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
34. Deep Learning Model With Game Theory-Based Gradient Explanations for Retinal Images
    Kanupriya Mittal, V. Mary Anita Rajam · 2023 · Lecture notes on data engineering and communications technologies
35. Beyond Predictions: Explainability and Learning from Machine Learning
    Chih-Ying Deng, Akinori Mitani, Christina Chen, Lily H. Peng, Naama Hammel, Yun Liu · 2023 · Springer eBooks
36. Comparison of Explainable Machine-Learning Models for Decision-Making in Health Intensive Care Using SHapley Additive exPlanations
    Igor Pereira Vidal, Marluce Rodrigues Pereira, André Pimenta Freire, Uanderson Resende, Erick Galani Maziero · 2023 · Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI)
37. Impact of Artificial Intelligence and Communication Tools in Veterinary and Medical Sciences
    Muhammad Rizwan Saeed, Muhammad Abdullah, Muhammad Zoraiz, Waqas Ahmad, Muhammad Ahsan Naeem, Qaiser Akram, Muhammad Younus · 2023 · Advances in linguistics and communication studies
38. Using an interpretable amino acid-based machine learning method to enhance the diagnosis of major depressive disorder
    Cyrus S. H. Ho, Trevor Wei Kiat Tan, Yee Ling Chan · 2023 · Research Square
39. GrMC: Towards Interpretable Classification Models That Are Also Accurate
    Guozhu Dong, Nicholas Skapura · 2023 · IEEE International Conference on Knowledge Graph (ICKG)
40. A predictive atlas of disease onset from retinal fundus photographs
    Thore Buergel, Lukas Loock, Jakob Steinfeldt, Laura Hoffmann, Steffen Emil Künzel, Julius Upmeier zu Belzen, Anthony P. Khawaja, Robert Luben, Paul J. Foster, Claudia Langenberg et al. · 2024 · medRxiv
41. Digital Transformation Using Industry 4.0 and Artificial Intelligence
    M. Keerthika, M. Pragadeesh, M. Santhiya, G. Belshia Jebamalar, Harish Venu · 2024 · Wiley eBooks
42. Human Intention Recognition for Trauma Resuscitation: An Interpretable Deep Learning Approach for Medical Process Data
    Keyi Li, Mary S. Kim, Sen Yang · 2024 · SSRN Electronic Journal
43. Building interpretable predictive model for hospital readmission
    Nor Hamizah Miswan, Roslinda Mohd Nazar, Chan Chee Seng · 2024 · AIP conference proceedings
44. Identifying influential individuals and predicting future demand of chronic kidney disease patients
    Zlatana D. Nenova, Valerie L. Bartelt · 2024 · Decision Sciences
45. Analyzing the Effectiveness of Smartphone Applications on Disease Management and Healthcare Systems
    Rabei Raad Ali, Wisam Subhi Al-Dayyeni, Christy Atika Sari, Eko Hari Rachmawanto, Siti Salwani Binti Yaacob, Omar M. Jihad · 2024 · IEEE International Conference on Application of Information and Communication Technologies (AICT)
46. Social Determinants of Healthy Aging: An Investigation using the All of Us Cohort
    Wei‐Han Chen, Yao-An Lee, Huilin Tang, Chenyu Li, Ying Lu, Yu Huang, Rui Yin, Melissa J. Armstrong, Yang Yang, Gregor Štiglic et al. · 2025 · medRxiv
47. A formal corpus of mathematical theorems: a bridge from natural language to first-order logic
    Lulu Li, Zhengtao Li, Peng Hu, Hao Zhang · 2024 · International Conference on Computing and Pattern Recognition (ICCPR)
48. The Role of Machine Learning in Crafting a Predictive Data Strategy
    Naveen Kumar · 2020 · International Journal of Scientific Research in Science Engineering and Technology
49. Machine Learning for Smart Healthcare Industry: A Succinct Review
    Chander Prabha, Prakash Srivastava, Harimohan Dixit · 2024 · International Conference on Sustainable Communication Networks and Application (ICSCNA)
50. Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion
    Ezequiel Juarez Garcia, Chad L. Stephens, Nicholas J. Napoli · 2025 · AIAA SciTech Forum
51. A Simple and Interpretable Deep Learning Model for Diagnosing Pneumonia from Chest X-Ray Images
    Lucas Otávio L. Silva, Karine Marques Hara, Pedro Henrique Mendes de Paula · 2025 · Lecture notes in computer science
52. Cloud Computing Based Diabetes Prediction Framework with Risk Factor Analysis
    Muhammed Golec, Awanish Kumar Sinha, Han Wang · 2025 · Engineering cyber-physical systems and critical infrastructures
53. Predictive Insights for Personalising Esophagogastric Cancer Treatment Process - A Case Study
    Mozhgan Vazifehdoostirani, Andrei Buliga, Laura Genga · 2025 · Lecture notes in business information processing
54. Big Data in Bioinformatics
    Naveed Jeelani Khan, Kamil Reza Khondakar, Asif Adil · 2025 · Advances in medical technologies and clinical practice book series
55. Enhancing Medical Image Diagnosis Accuracy Using Hybrid Convolutional Neural Networks and Explainable AI Techniques
    Santosh Kumar Jha · 2025 · International Journal of Advanced Research in Science Communication and Technology
56. The Crucial Role of Predictive Models in Childhood Asthma care: Improving Outcomes Through Data-Driven Insights
    Aditya Chakraborty, AKM R Bashar · 2025 · medRxiv
57. Predicting 28-Day Mortality in Critically Ill Patients Receiving Continuous Renal Replacement Therapy: A Novel Interpretable Machine Learning Approach
    Tao Zhang, Zi-Han Nan, Xiaoxuan Fan, Jing-Xiao Pang, Congcong Zhao, Xin Yan, Zhenjie Hu, Shaohan Guo · 2025 · Journal of Multidisciplinary Healthcare
58. Evaluation of Mutiple Classical Machine Learning Models for Breast Tumor Classification
    Xiaohan Hu · 2025 · IEEE International Conference on Image Processing and Computer Applications (ICIPCA)
59. Frequency-Modulated Transformer Self-Attention for Advanced Infectious Disease Prediction
    Asmita Mahajan, Durga Toshniwal · 2025 · ACM Transactions on Intelligent Systems and Technology
60. Beyond the hype: exploring the impact, challenges, and potential of large language models in healthcare
    Hafiz Farooq Ahmad, Junaid Sajid, Raihan Ur Rasool, Asad Waqar Malik · 2025 · Cluster Computing
61. DWT-Based Epileptic Seizure Detection Using Fuzzy Logic Model with Entropy and Table Lookup Scheme
    Alireza Mohammadi, Arvin Esfandiari, Ali Doustmohammadi · 2025
62. Domain-adapted explainability for machine learning predictions of rotodynamic pump degradation in safety-critical industrial sectors
    Omnia Amin, Blair Brown, Bruce Stephen, Valerie Livina, S.D.J. McArthur · 2025 · Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy
63. SCM-4-OSA: An End-to-End Explainable Deep Learning Model for Interpretable Obstructive Sleep Apnea Detection Based on Cyclic Variation of Heart Rate in ECG
    Weinan Wang, Kevin L. Kilgore, Laleh Najafizadeh · 2025
64. Interpretability vs . Efficiency in ApplicationSpecific Analytics
    Rahul Oberoi, Sachin Kumar Gupta, Bhoomi Gupta · 2025 · BENTHAM SCIENCE PUBLISHERS eBooks
65. Machine Learning for Threat Detection and Intrusion Prevention
    Muhammad Faisal, I Dewa Made Widia, Nizirwan Anwar, Titik Khawa Abdul Rahman, Aedah Binti Abd Rahman, Alders Paliling, Raden Teddy Iswahyudi, Anshika Sharma · 2025 · Advances in computational intelligence and robotics book series
66. Introduction: an overview
    Young-Seuk Park, Sven Eric Jørgensen · 2025 · Elsevier eBooks
67. Interpretable Machine Learning Prediction of Clostridioides difficile Infection Using Three-Year Longitudinal EHR Data
    John Peterson, Mark Reynolds, Kevin Brooks · 2022 · Interdisciplinary Research in Medical Sciences Specialty
68. Sleep Health Classification Based on Digital Device Usage and Lifestyle Behavior Using Machine Learning
    I. Fawwaz, A. M. Nababan, R. Anugrahwaty, Lois Pranata Sembiring, Muhammad Akbar · 2025 · International Conference on Computing and Artificial Intelligence
69. Integrating Artificial Intelligence for Plant Phenotyping
    Pawan Kumar Dash, Tushar Arun Mohanty · 2026 · Springer eBooks
70. A diagnosis tool for early detection and classification of heart disease in individuals using transformer mechanisms
    Saba Arif, Sang Hyeok Son, Hyun Yong Kim, Sang Chul Kim, Jong Yun Lee · 2026 · Computer Methods and Programs in Biomedicine
71. Interactive Digital Visualization Counseling for Lifestyle Change in Patients at Risk of Cardiovascular Diseases: Randomized Controlled Trial
    Adrijana Svenšek, Mateja Lorber, Zalika Klemenc–Ketiš, Lucija Gosak, Dominika Muršec, Gregor Štiglic · 2026 · JMIR Public Health and Surveillance
72. Architecting the Orthopedical Clinical AI Pipeline: A Review of Integrating Foundation Models and FHIR for Agentic Clinical Assistants and Digital Twins
    Assiya Boltaboyeva, Zhanel Baigarayeva, Баглан Иманбек, Bibars Amangeldy, Nurdaulet Tasmurzayev, Kassymbek Ozhikenov, Zhadyra N. Alimbayeva, Chingiz A. Alimbayev, Nurgul Karymsakova · 2026 · Algorithms
73. AI-Enabled ESG Scoring Models for Corporate Governance
    Ujan Pradhan, Vyomika Anand · 2026 · Advances in computational intelligence and robotics book series
74. Predicting Low Birth Weight in India Using Machine Learning Techniques: Insights from NFHS-5
    Vikas Kamble, Basil Edolikkandy · 2026 · Research Square
75. Restricted Receptive Fields for Face Verification
    Kağan Öztürk, Aman Bhatta, Haiyu Wu, Patrick J. Flynn, Kevin W. Bowyer · 2026 · IEEE Transactions on Biometrics Behavior and Identity Science
76. Risk Stratification for In-Hospital Mortality in Alzheimer’s Disease Using Interpretable Regression and Explainable AI
    Tursun Alkam, Ebrahim Tarshizi, Andrew H Van Benschoten · 2026 · Geriatrics
77. AI-Driven Data Analytics for Environmental Decision-Making
    Swagata Ashwani, Meetu Malhotra · 2026 · BENTHAM SCIENCE PUBLISHERS eBooks
78. BREATHE: Interpretable Stacked Hybrid Models for Multi-Disease Prediction of SO 2 -Linked Respiratory Illnesses in Kankoyo, a Mining Community in Zambia
    Sipiwe Chihana, J. Mbale, N. Chaamwe · 2026 · IEEE Access
79. AI-based systems for predicting surgical outcomes in complex cases
    Shekhar M. Kumbhar, Deepak Suresh Asudani, Natu Milind A. · 2026 · AIP conference proceedings
80. Deep learning interpretability with visual analytics : Exploring reasoning and bias exploitation
    Théo Jaunet · 2022 · theses.fr (ABES)
81. Machine Learning Techniques for Voice-Based Parkinson's Disease Detection
    Nishvika Teja Reddy, Niharika. N, Jayashree KR · 2026 · IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)
82. Mathematics of statistical sequential decision making : concentration, risk-awareness and modelling in stochastic bandits, with applications to bariatric surgery
    Patrick Saux · 2024 · theses.fr (ABES)
83. An interpretable deep learning framework for predictive modeling of postoperative infections in ICU patients
    Xiaoyu Wu, Isaac Luria, Meisheng Xiao, Patrick Tighe, Fei Zou, Baiming Zou · 2026 · PLoS ONE
84. Predicting post‐stroke dementia using sex‐specific risk factors: Development of an interpretable clinical scoring tool
    Chenyin Chu, Yihan Wang, Liwei Ma, Liang Jin, Yijun Pan · 2026 · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring
85. Investigating How Trading Patterns and Twitter Impact the CryptoPunks NFT Market
    Yuxiang Liu, Xinyu Feng, Mingdong Tang · 2026 · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
86. Deep Performance Analysis in the Interpretability and Explicability of Artificial Intelligence (XAI)
    Imane Aitouhanni, Amine Berqia, Hajar Fares, Habiba Bouijij, Yassine Mouniane, Amol Dattatraya Vibhute · 2026 · Wiley eBooks
87. Explainable artificial intelligence (XAI) in geotechnical engineering
    Zong Woo Geem, Gebrai̇l Bekdaş, Si̇nan Melih Ni̇gdeli, Yaren Aydın, Ümit Işıkdağ, Tae-Hyung Kim · 2026 · Elsevier eBooks
88. FairED: An Open Benchmarking Framework for Reproducible Evaluation of Algorithmic Fairness in Emergency Care Across Clinical Sites
    Xinnie Mai, Yunqian Liu, Yilin Ning, David A. Wacker, Mingquan Lin, Nan Liu, Michael A. Puskarich, Feng Xie · 2026 · Research Square
89. Compound-Scaled EfficientNetB5 Model for Reliable Multi-Class Colon Disease Image Classification
    Renu Arya, Bura Vijay Kumar, Reena Vohra Saini · 2026 · International Conference on Computing for Sustainable Global Development
90. Predicting amyloid status in Primary Progressive Aphasia using explainable artificial intelligence
    Cole Robertson, Daisy Hochberg, Megan Quimby, Phillip Wolff, Bradford Clark Dickerson, Neguine Rezaii · 2026 · npj Dementia
91. Using Explainable Machine Learning to Identify Determinants of Spinal Deformities in Children: It’s Not Only About What, but Also About How
    Dragica Bukumirić, Aleksandra Ilić, Mirjana Pajčin et al. · 2026 · Healthcare
92. A Hybrid Machine Learning and Automata-Based Explainable Clinical Decision Support
    Supriya Pande, Anjali Gavit, Pranjal Pagar, Tanuja Pardeshi, Rajashri Rikame, Mritunjay Kr. Ranjan · 2026 · International Conference on Recent Trends in Computer Science and Technology (ICRTCST)
93. Tree based Ensemble Methods for Pima Diabetes Prediction
    B. Gopal Samy, R. Sethu Ritheesh, I. Raashibha Sherin · 2026 · International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)
94. Computational Pipelines for Disease-Specific Drug Repurposing
    Mena Abdelsayed · 2026 · Pharmaceutical science.
95. Machine Learning Prediction of Healthcare Utilization Using National Open Primary Care Clinic Data
    Gulnura Kalbagayeva · 2026 · West Kazakhstan Public Health Journal
96. Multi-Output Machine Learning and RAG: A Decoupled Architecture for Privacy-Preserving Dermatological Assessment
    Yassine Benachour, Samuel Tadesse Awlew, Mathias Worku Beshah, Eyob Shimelis Asfaw · 2026 · International Conference on Interactive Systems & Information Society Technologies (InterSys)
97. From Curiosity to Caution: How Expertise Shapes the Use of Interpretable Machine Learning
    Sameer Naqvi, Gayathri Balaji, Angelique Laju, Harmanpreet Kaur · 2026 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
98. Pharmacoepidemiology unpacked: a roadmap for junior researchers
    Alyaa M. Ajabnoor · 2026 · Frontiers in Pharmacology
99. Necesidad insatisfecha en anticoncepción en población racializada en Colombia: análisis de resultados de la Encuesta Nacional de Demografía y Salud de 2015
    Lina Rodriguez-Aponte, Jorge Martín Rodríguez, Fernando Ruiz-Vallejo · 2026 · Cadernos de Saúde Pública
100. Interpretability vs Accuracy: Stability Using SHAP Explanations Under Noisy Training Data
     Anurag Yadav, Gaurav Bathla, Vikas Wasoon · 2026 · International Conference on AI, Data Science, Cyber Security and Smart Manufacturing for Sustainable Development (ICADCS)