{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T17:35:31Z","timestamp":1784828131177,"version":"3.55.0"},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"6","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2025,12,31]]},"abstract":"<jats:p>\n            Cyber twin technology, a successful branch of simulation modeling in business, is now being applied in the healthcare sector. An intelligent architecture inspired by cyber twins is proposed to explore the unique visual, behavioral, and physiological experiences of individuals with anxiety disorders while working in smart office environments. Temporal data mining is utilized for framing data granules, and quantum probability techniques are employed for anomaly detection within the framework. Additionally, a novel multilayer Convolutional Neural Network is introduced to predict a quantifiable Health Vulnerability Index. A smart alert system is included, capable of notifying caregivers of any identified health concerns, enabling timely assistance. To evaluate the effectiveness of the proposed strategy, it was tested on real-world data comprising 82,235 cases. The results demonstrate that the method excels in several key performance metrics: time efficiency (24.6\u2009seconds), classification efficiency (Precision (92.77%), Specificity (92.43%), and Sensitivity (92.82%)), decision-making efficiency (\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(r^{2}=79%\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            ), error rate (AAE 0.31%), and stability (75%), surpassing current state-of-the-art methodologies.\n          <\/jats:p>","DOI":"10.1145\/3759253","type":"journal-article","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T15:17:13Z","timestamp":1754493433000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence-Inspired Anxiety Detection in Smart Office: Cyber Twin Perspective"],"prefix":"10.1145","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9878-7646","authenticated-orcid":false,"given":"Munish","family":"Bhatia","sequence":"first","affiliation":[{"name":"Department of Computer Applications, National Institute of Technology, Kurukshetra, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2022.121570"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/informatics8040075"},{"key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1007\/s11904-021-00578-7","article-title":"Novel platforms for biomedical HIV prevention delivery to key populations\u2014Community mobile clinics, peer-supported, pharmacy-led prep delivery, and the use of telemedicine","volume":"18","author":"Rousseau E.","year":"2021","unstructured":"E. Rousseau, R. Julies, N. Madubela, and S. Kassim. 2021. Novel platforms for biomedical HIV prevention delivery to key populations\u2014Community mobile clinics, peer-supported, pharmacy-led prep delivery, and the use of telemedicine. Current HIV\/AIDS Reports 18 (2021), 500\u2013507.","journal-title":"Current HIV\/AIDS Reports"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics11040607"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3177278"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1177\/21650799221079045"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1097\/NAQ.0000000000000499"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare10101993"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2019.01.003"},{"issue":"4","key":"e_1_3_2_11_2","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1176\/appi.ps.202000189","article-title":"Evidence for use of cannabinoids in mood disorders, anxiety disorders, and PTSD: A systematic review","volume":"72","author":"Stanciu C. N.","year":"2021","unstructured":"C. N. Stanciu, M. F. Brunette, N. Teja, and A. J. Budney. 2021. Evidence for use of cannabinoids in mood disorders, anxiety disorders, and PTSD: A systematic review. Psychiatric Services (Washington, D.C.) 72, 4 (2021), 429\u2013436.","journal-title":"Psychiatric Services (Washington, D.C.)"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpr.2020.101952"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3096672"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2022.02.005"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2014.2302638"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.3390\/su16156311"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2023.1307823"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1155\/2024\/2387983"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-024-13242-5"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3382011"},{"issue":"38","key":"e_1_3_2_21_2","doi-asserted-by":"crossref","first-page":"85849","DOI":"10.1007\/s11042-024-20073-6","article-title":"Decision-based framework to facilitate EDGE computing in smart health care","volume":"83","author":"Singh S.","year":"2024","unstructured":"S. Singh, M. Sajwan, and S. Kukreja. 2024. Decision-based framework to facilitate EDGE computing in smart health care. Multimedia Tools and Applications 83, 38 (2024), 85849\u201385869.","journal-title":"Multimedia Tools and Applications"},{"key":"e_1_3_2_22_2","doi-asserted-by":"crossref","first-page":"10769","DOI":"10.1109\/ACCESS.2024.3354854","article-title":"DeepDiabetic: An identification system of diabetic eye diseases using deep neural networks","volume":"12","author":"Albelaihi A.","year":"2024","unstructured":"A. Albelaihi and D. M. Ibrahim. 2024. DeepDiabetic: An identification system of diabetic eye diseases using deep neural networks. IEEE Access 12 (2024), 10769\u201310789.","journal-title":"IEEE Access"},{"issue":"6","key":"e_1_3_2_23_2","first-page":"e1552","article-title":"Medical intelligence for anxiety research: Insights from genetics, hormones, implant science, and smart devices with future strategies","volume":"14","author":"Akhtar F.","year":"2024","unstructured":"F. Akhtar, M. Belal Bin Heyat, A. Sultana, S. Parveen, H. Muhammad Zeeshan, S. F. Merlin, B. Shen, D. Pomary, J. Ping Li, and M. Sawan. 2024. Medical intelligence for anxiety research: Insights from genetics, hormones, implant science, and smart devices with future strategies. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 14, 6 (2024), e1552.","journal-title":"Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"},{"issue":"9","key":"e_1_3_2_24_2","doi-asserted-by":"crossref","first-page":"25951","DOI":"10.1007\/s11042-023-16564-7","article-title":"Depression detection based on social networking sites using data mining","volume":"83","author":"Pande S. D.","year":"2024","unstructured":"S. D. Pande, S. Hasane Ahammad, M. N. Gurav, O. S. Faragallah, M. M. Eid, and A. N. Z. Rashed. 2024. Depression detection based on social networking sites using data mining. Multimedia Tools and Applications 83, 9 (2024), 25951\u201325967.","journal-title":"Multimedia Tools and Applications"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2024.109012"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-15827-7"},{"key":"e_1_3_2_27_2","doi-asserted-by":"crossref","first-page":"174591","DOI":"10.1109\/ACCESS.2024.3502077","article-title":"A digital twin-based platform for medical cyber-physical systems","volume":"12","author":"Rahim M.","year":"2024","unstructured":"M. Rahim, W. Lalouani, E. Toubal, and L. Emokpae. 2024. A digital twin-based platform for medical cyber-physical systems. IEEE Access 12 (2024), 174591\u2013174607.","journal-title":"IEEE Access"},{"key":"e_1_3_2_28_2","first-page":"149","volume-title":"Handbook of Digital Twins","author":"Wang D.","unstructured":"D. Wang, D. Chen, Y. Zhu, and Z. Han. Digital twin for federated analytics applications. In Handbook of Digital Twins. Zhihan Lyu (Ed.), CRC Press, 149\u2013166."},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.3390\/quantum5020033"},{"key":"e_1_3_2_30_2","first-page":"1","article-title":"Optimized feedforward neural network for error reduction in medical Internet of Things","volume":"99","author":"Mukisa K. J.","year":"2024","unstructured":"K. J. Mukisa, L. A. C. Ahakonye, D.-S. Kim, and J. M. Lee. 2024. Optimized feedforward neural network for error reduction in medical Internet of Things. Recall 99, 2024 (2024), 1\u20133.","journal-title":"Recall"},{"issue":"12","key":"e_1_3_2_31_2","doi-asserted-by":"crossref","first-page":"4190","DOI":"10.1109\/TMI.2024.3417007","article-title":"PolarFormer: A transformer-based method for multi-lesion segmentation in intravascular OCT","volume":"43","author":"Huang Z.","year":"2024","unstructured":"Z. Huang, J. Sun, Y. Shao, Z. Wang, S. Wang, Q. Li, J. Li, and Q. Yu. 2024. PolarFormer: A transformer-based method for multi-lesion segmentation in intravascular OCT. IEEE Transactions on Medical Imaging 43, 12 (2024), 4190\u20134199.","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jsams.2023.01.009"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jechem.2023.08.047"}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3759253","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:38:52Z","timestamp":1760708332000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3759253"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,17]]},"references-count":32,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,12,31]]}},"alternative-id":["10.1145\/3759253"],"URL":"https:\/\/doi.org\/10.1145\/3759253","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"value":"2157-6904","type":"print"},{"value":"2157-6912","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,17]]},"assertion":[{"value":"2024-04-29","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-31","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-17","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}