{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T15:44:17Z","timestamp":1788277457493,"version":"build-2803163510"},"publisher-location":"New York, NY, USA","reference-count":51,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,2,14]],"date-time":"2022-02-14T00:00:00Z","timestamp":1644796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,2,14]]},"DOI":"10.1145\/3511616.3513112","type":"proceedings-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:21:13Z","timestamp":1647908473000},"page":"168-175","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Predictive risk modelling in mental health issues using machine learning on graphs"],"prefix":"10.1145","author":[{"given":"Haohui","family":"Lu","sequence":"first","affiliation":[{"name":"The University of Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahadat","family":"Uddin","sequence":"additional","affiliation":[{"name":"The University of Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farshid","family":"Hajati","sequence":"additional","affiliation":[{"name":"Victoria University (Sydney), Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matloob","family":"Khushi","sequence":"additional","affiliation":[{"name":"The University of Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Ali","family":"Moni","sequence":"additional","affiliation":[{"name":"University of Queensland, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,3,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Retrieved","author":"Organisation World Health","year":"2021","unstructured":"World Health Organisation . 2021 . Mental Health . Retrieved August 10, 2021 from https:\/\/www.who.int\/health-topics\/mental-health World Health Organisation. 2021. Mental Health. Retrieved August 10, 2021 from https:\/\/www.who.int\/health-topics\/mental-health"},{"key":"e_1_3_2_1_2_1","volume-title":"Chronic disease. Retrieved","author":"Australian Institute of Health and Welfare (AIHW). 2021.","year":"2021","unstructured":"Australian Institute of Health and Welfare (AIHW). 2021. Chronic disease. Retrieved July 6, 2021 from https:\/\/www.aihw.gov.au\/reports-data\/health-conditions-disability-deaths\/chronic-disease\/overview. Australian Institute of Health and Welfare (AIHW). 2021. Chronic disease. Retrieved July 6, 2021 from https:\/\/www.aihw.gov.au\/reports-data\/health-conditions-disability-deaths\/chronic-disease\/overview."},{"key":"e_1_3_2_1_3_1","volume-title":"Mental health services in Australia. Retrieved","author":"Australian Institute of Health and Welfare (AIHW). 2021.","year":"2021","unstructured":"Australian Institute of Health and Welfare (AIHW). 2021. Mental health services in Australia. Retrieved July 6, 2021 from https:\/\/www.aihw.gov.au\/reports\/mental-health-services\/mental-health-services-in-australia\/report-contents\/summary-of-mental-health-services-in-australia Australian Institute of Health and Welfare (AIHW). 2021. Mental health services in Australia. Retrieved July 6, 2021 from https:\/\/www.aihw.gov.au\/reports\/mental-health-services\/mental-health-services-in-australia\/report-contents\/summary-of-mental-health-services-in-australia"},{"key":"e_1_3_2_1_4_1","unstructured":"Benjamin G Druss and Elizabeth Reisinger Walker. 2011. Mental disorders and medical comorbidity.\u00a0The Synthesis project. Research synthesis report 21 1\u201326.  Benjamin G Druss and Elizabeth Reisinger Walker. 2011. Mental disorders and medical comorbidity.\u00a0The Synthesis project. Research synthesis report 21 1\u201326."},{"key":"e_1_3_2_1_5_1","volume-title":"Richard Scoville and Roger Taylor","author":"Hillestad Richard","year":"2005","unstructured":"Richard Hillestad , James Bigelow , Anthony Bower , Federico Girosi , Robin Meili , Richard Scoville and Roger Taylor . 2005 . Can Electronic Medical Record Systems Transform Health Care? Potential Health Benefits, Savings, and Costs. Health affairs 24, 5, 1103-1117. Richard Hillestad, James Bigelow, Anthony Bower, Federico Girosi, Robin Meili, Richard Scoville and Roger Taylor. 2005. Can Electronic Medical Record Systems Transform Health Care? Potential Health Benefits, Savings, and Costs. Health affairs 24, 5, 1103-1117."},{"key":"e_1_3_2_1_6_1","volume-title":"Ho-Cheol Kim and Dilip V Jeste","author":"Graham Sarah","year":"2019","unstructured":"Sarah Graham , Colin Depp , Ellen E Lee , Camille Nebeker , Xin Tu , Ho-Cheol Kim and Dilip V Jeste . 2019 . Artificial Intelligence for Mental Health and Mental Illnesses: An Overview . Current psychiatry reports 21, 11, 1-18. Sarah Graham, Colin Depp, Ellen E Lee, Camille Nebeker, Xin Tu, Ho-Cheol Kim and Dilip V Jeste. 2019. Artificial Intelligence for Mental Health and Mental Illnesses: An Overview. Current psychiatry reports 21, 11, 1-18."},{"key":"e_1_3_2_1_7_1","volume-title":"Delyse M Hutchinson and Samantha J Teague","author":"Shatte Adrian BR","year":"2019","unstructured":"Adrian BR Shatte , Delyse M Hutchinson and Samantha J Teague . 2019 . Machine Learning in Mental Health : A Scoping Review of Methods and Applications. Psychological medicine 49, 9, 1426-1448. Adrian BR Shatte, Delyse M Hutchinson and Samantha J Teague. 2019. Machine Learning in Mental Health: A Scoping Review of Methods and Applications. Psychological medicine 49, 9, 1426-1448."},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 41-47","author":"Prajwal V.","year":"2018","unstructured":"Arun, Vanishri, V. Prajwal , Murali Krishna , B. V. Arunkumar , S. K. Padma , and V. Shyam . 2018 A Boosted Machine Learning Approach for Detection of Depression . In Proceedings of 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 41-47 . http:\/\/dx.doi.org\/10.1109\/SSCI. 2018 .8628945 10.1109\/SSCI.2018.8628945 Arun, Vanishri, V. Prajwal, Murali Krishna, B. V. Arunkumar, S. K. Padma, and V. Shyam. 2018 A Boosted Machine Learning Approach for Detection of Depression. In Proceedings of 2018 IEEE Symposium Series on Computational Intelligence (SSCI). 41-47. http:\/\/dx.doi.org\/10.1109\/SSCI.2018.8628945"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2018.01.019"},{"key":"e_1_3_2_1_10_1","volume-title":"Caitlin Thompson and Robert M. Bossarte","author":"Kessler Ronald C.","year":"2017","unstructured":"Ronald C. Kessler , Irving Hwang , Claire A. Hoffmire , John F. McCarthy , Maria V. Petukhova , Anthony J. Rosellini , Nancy A. Sampson , Alexandra L. Schneider , Paul A. Bradley , Ira R. Katz , Caitlin Thompson and Robert M. Bossarte . 2017 . Developing a practical suicide risk prediction model for targeting high-risk patients in the Veterans health Administration .\u00a0International journal of methods in psychiatric research,\u00a026,3, e1575. https:\/\/doi.org\/10.1002\/mpr.1575 10.1002\/mpr.1575 Ronald C. Kessler, Irving Hwang, Claire A. Hoffmire, John F. McCarthy, Maria V. Petukhova, Anthony J. Rosellini, Nancy A. Sampson, Alexandra L. Schneider, Paul A. Bradley, Ira R. Katz, Caitlin Thompson and Robert M. Bossarte. 2017. Developing a practical suicide risk prediction model for targeting high-risk patients in the Veterans health Administration.\u00a0International journal of methods in psychiatric research,\u00a026,3, e1575. https:\/\/doi.org\/10.1002\/mpr.1575"},{"key":"e_1_3_2_1_11_1","volume-title":"Desmond J Oathes and Amit Etkin","author":"Drysdale Andrew T","year":"2017","unstructured":"Andrew T Drysdale , Logan Grosenick , Jonathan Downar , Katharine Dunlop , Farrokh Mansouri , Yue Meng , Robert N Fetcho , Benjamin Zebley , Desmond J Oathes and Amit Etkin . 2017 . Resting-State Connectivity Biomarkers Define Neurophysiological Subtypes of Depression. Nature medicine 23, 1, 28-38. Andrew T Drysdale, Logan Grosenick, Jonathan Downar, Katharine Dunlop, Farrokh Mansouri, Yue Meng, Robert N Fetcho, Benjamin Zebley, Desmond J Oathes and Amit Etkin. 2017. Resting-State Connectivity Biomarkers Define Neurophysiological Subtypes of Depression. Nature medicine 23, 1, 28-38."},{"key":"e_1_3_2_1_12_1","volume-title":"Andrew J Greenshaw, Serdar M Dursun and Ganesan Venkatasubramanian.","author":"Kalmady Sunil Vasu","year":"2019","unstructured":"Sunil Vasu Kalmady , Russell Greiner , Rimjhim Agrawal , Venkataram Shivakumar , Janardhanan C Narayanaswamy , Matthew RG Brown , Andrew J Greenshaw, Serdar M Dursun and Ganesan Venkatasubramanian. 2019 . Towards Artificial Intelligence in Mental Health by Improving Schizophrenia Prediction with Multiple Brain Parcellation Ensemble-Learning. npj Schizophrenia 5, 1, 1-11. Sunil Vasu Kalmady, Russell Greiner, Rimjhim Agrawal, Venkataram Shivakumar, Janardhanan C Narayanaswamy, Matthew RG Brown, Andrew J Greenshaw, Serdar M Dursun and Ganesan Venkatasubramanian. 2019. Towards Artificial Intelligence in Mental Health by Improving Schizophrenia Prediction with Multiple Brain Parcellation Ensemble-Learning. npj Schizophrenia 5, 1, 1-11."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/5238028"},{"key":"e_1_3_2_1_14_1","volume-title":"John Hinkle and Adam Hanina","author":"Bain Earle E","year":"2017","unstructured":"Earle E Bain , Laura Shafner , David P Walling , Ahmed A Othman , Christy Chuang-Stein , John Hinkle and Adam Hanina . 2017 . Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects with Schizophrenia. JMIR mHealth and uHealth 5, 2, e18. Earle E Bain, Laura Shafner, David P Walling, Ahmed A Othman, Christy Chuang-Stein, John Hinkle and Adam Hanina. 2017. Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects with Schizophrenia. JMIR mHealth and uHealth 5, 2, e18."},{"key":"e_1_3_2_1_15_1","first-page":"739","volume-title":"Proceedings of 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG","author":"Kacem Anis","year":"2018","unstructured":"Anis Kacem , Zakia Hammal , Mohamed Daoudi and Jeffrey Cohn . Year. Detecting Depression Severity by Interpretable Representations of Motion Dynamics . In Proceedings of 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018 ). IEEE, 739 - 745 . Anis Kacem, Zakia Hammal, Mohamed Daoudi and Jeffrey Cohn. Year. Detecting Depression Severity by Interpretable Representations of Motion Dynamics. In Proceedings of 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018). IEEE, 739-745."},{"key":"e_1_3_2_1_16_1","volume-title":"Michael Rufer and Steffi Weidt","author":"Wahle Fabian","year":"2016","unstructured":"Fabian Wahle , Tobias Kowatsch , Elgar Fleisch , Michael Rufer and Steffi Weidt . 2016 . Mobile Sensing and Support for People with Depression : A Pilot Trial in the Wild. JMIR mHealth and uHealth 4, 3, e5960. Fabian Wahle, Tobias Kowatsch, Elgar Fleisch, Michael Rufer and Steffi Weidt. 2016. Mobile Sensing and Support for People with Depression: A Pilot Trial in the Wild. JMIR mHealth and uHealth 4, 3, e5960."},{"key":"e_1_3_2_1_17_1","volume-title":"Benny Lo and Guang-Zhong Yang","author":"Rav\u00ec Daniele","year":"2016","unstructured":"Daniele Rav\u00ec , Charence Wong , Fani Deligianni , Melissa Berthelot , Javier Andreu-Perez , Benny Lo and Guang-Zhong Yang . 2016 . Deep Learning for Health Informatics. IEEE journal of biomedical and health informatics 21, 1, 4-21. Daniele Rav\u00ec, Charence Wong, Fani Deligianni, Melissa Berthelot, Javier Andreu-Perez, Benny Lo and Guang-Zhong Yang. 2016. Deep Learning for Health Informatics. IEEE journal of biomedical and health informatics 21, 1, 4-21."},{"key":"e_1_3_2_1_18_1","volume-title":"Tat Seng Chua and Wendy Hall. Year. Cross-Domain Depression Detection Via Harvesting Social Media. In Proceedings of International Joint Conferences on Artificial Intelligence. 1611-1617","author":"Shen Tiancheng","year":"2018","unstructured":"Tiancheng Shen , Jia Jia , Guangyao Shen , Fuli Feng , Xiangnan He , Huanbo Luan , Jie Tang , Thanassis Tiropanis , Tat Seng Chua and Wendy Hall. Year. Cross-Domain Depression Detection Via Harvesting Social Media. In Proceedings of International Joint Conferences on Artificial Intelligence. 1611-1617 . https:\/\/doi.org\/10.24963\/ijcai. 2018 \/223 10.24963\/ijcai.2018 Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Thanassis Tiropanis, Tat Seng Chua and Wendy Hall. Year. Cross-Domain Depression Detection Via Harvesting Social Media. In Proceedings of International Joint Conferences on Artificial Intelligence. 1611-1617. https:\/\/doi.org\/10.24963\/ijcai.2018\/223"},{"key":"e_1_3_2_1_19_1","volume-title":"Proceedings of Proceedings of the AAAI Conference on Artificial Intelligence. 110-117","author":"Gui Tao","unstructured":"Tao Gui , Liang Zhu , Qi Zhang , Minlong Peng , Xu Zhou , Keyu Ding and Zhigang Chen . Year. Cooperative Multimodal Approach to Depression Detection in Twitter . In Proceedings of Proceedings of the AAAI Conference on Artificial Intelligence. 110-117 . https:\/\/doi.org\/10.1609\/aaai.v33i01.3301110 10.1609\/aaai.v33i01.3301110 Tao Gui, Liang Zhu, Qi Zhang, Minlong Peng, Xu Zhou, Keyu Ding and Zhigang Chen. Year. Cooperative Multimodal Approach to Depression Detection in Twitter. In Proceedings of Proceedings of the AAAI Conference on Artificial Intelligence. 110-117. https:\/\/doi.org\/10.1609\/aaai.v33i01.3301110"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103610"},{"key":"e_1_3_2_1_21_1","volume-title":"Bharuno Mahesworo and James Baurley","author":"Pardamean Bens","year":"2020","unstructured":"Bens Pardamean , Haryono Soeparno , Arif Budiarto , Bharuno Mahesworo and James Baurley . 2020 . Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health. Healthcare informatics research 26, 2, 83-92. https:\/\/doi.org\/10.4258\/hir.2020.26.2.83 10.4258\/hir.2020.26.2.83 Bens Pardamean, Haryono Soeparno, Arif Budiarto, Bharuno Mahesworo and James Baurley. 2020. Quantified Self-Using Consumer Wearable Device: Predicting Physical and Mental Health. Healthcare informatics research 26, 2, 83-92. https:\/\/doi.org\/10.4258\/hir.2020.26.2.83"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of Proceedings of the Australasian Computer Science Week Multiconference. 1-7. https:\/\/doi.org\/10","author":"Khan Arif","unstructured":"Arif Khan , Shahadat Uddin and Uma Srinivasan . Year. Adapting Graph Theory and Social Network Measures on Healthcare Data: A New Framework to Understand Chronic Disease Progression . In Proceedings of Proceedings of the Australasian Computer Science Week Multiconference. 1-7. https:\/\/doi.org\/10 .1145\/2843043.2843380 10.1145\/2843043.2843380 Arif Khan, Shahadat Uddin and Uma Srinivasan. Year. Adapting Graph Theory and Social Network Measures on Healthcare Data: A New Framework to Understand Chronic Disease Progression. In Proceedings of Proceedings of the Australasian Computer Science Week Multiconference. 1-7. https:\/\/doi.org\/10.1145\/2843043.2843380"},{"key":"e_1_3_2_1_23_1","volume-title":"Aswin Ratheesh and Brian O'Donoghue","author":"McGorry Patrick D","year":"2018","unstructured":"Patrick D McGorry , Aswin Ratheesh and Brian O'Donoghue . 2018 . Early Intervention\u2014an Implementation Challenge for 21st Century Mental Health Care. JAMA psychiatry 75, 6, 545-546. https:\/\/doi.org\/10.1001\/jamapsychiatry.2018.0621 10.1001\/jamapsychiatry.2018.0621 Patrick D McGorry, Aswin Ratheesh and Brian O'Donoghue. 2018. Early Intervention\u2014an Implementation Challenge for 21st Century Mental Health Care. JAMA psychiatry 75, 6, 545-546. https:\/\/doi.org\/10.1001\/jamapsychiatry.2018.0621"},{"key":"e_1_3_2_1_24_1","volume-title":"CBHS Health Funds. Retrieved","author":"Commonwealth Bank Health Society","year":"2021","unstructured":"Commonwealth Bank Health Society . 2021. CBHS Health Funds. Retrieved July 9, 2021 from www.cbhs.com.au\/. Commonwealth Bank Health Society. 2021. CBHS Health Funds. Retrieved July 9, 2021 from www.cbhs.com.au\/."},{"key":"e_1_3_2_1_25_1","unstructured":"The Australian Classification of Health Interventions. 2020. ICD-10-AM. Retrieved July 9 2021 from https:\/\/meteor.aihw.gov.au\/content\/index.phtml\/itemId\/641373  The Australian Classification of Health Interventions. 2020. ICD-10-AM. Retrieved July 9 2021 from https:\/\/meteor.aihw.gov.au\/content\/index.phtml\/itemId\/641373"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1097\/00005650-199801000-00004"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9681(87)90171-8"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5694\/mja17.00878"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.mlr.0000182534.19832.83"},{"key":"e_1_3_2_1_30_1","volume-title":"Mat\u00fa\u0161 Medo and Yi-Cheng Zhang","author":"Zhou Tao","year":"2007","unstructured":"Tao Zhou , Jie Ren , Mat\u00fa\u0161 Medo and Yi-Cheng Zhang . 2007 . Bipartite Network Projection and Personal Recommendation. Physical review E 76, 4, 046115. Tao Zhou, Jie Ren, Mat\u00fa\u0161 Medo and Yi-Cheng Zhang. 2007. Bipartite Network Projection and Personal Recommendation. Physical review E 76, 4, 046115."},{"key":"e_1_3_2_1_31_1","first-page":"515","volume-title":"Comorbidity: A Multidimensional Approach. Trends in molecular medicine 19, 9","author":"Capobianco Enrico","year":"2013","unstructured":"Enrico Capobianco . 2013 . Comorbidity: A Multidimensional Approach. Trends in molecular medicine 19, 9 , 515 - 521 . Enrico Capobianco. 2013. Comorbidity: A Multidimensional Approach. Trends in molecular medicine 19, 9, 515-521."},{"key":"e_1_3_2_1_32_1","volume-title":"Helen Christensen and Philip B Mitchell","author":"Harvey Samuel B","year":"2017","unstructured":"Samuel B Harvey , Matthew Modini , Sadhbh Joyce , Josie S Milligan-Saville , Leona Tan , Arnstein Mykletun , Richard A Bryant , Helen Christensen and Philip B Mitchell . 2017 . Can Work Make You Mentally Ill? A Systematic Meta-Review of Work-Related Risk Factors for Common Mental Health Problems. Occupational and environmental medicine 74, 4, 301-310. https:\/\/doi.org\/10.1136\/oemed-2016-104015 10.1136\/oemed-2016-104015 Samuel B Harvey, Matthew Modini, Sadhbh Joyce, Josie S Milligan-Saville, Leona Tan, Arnstein Mykletun, Richard A Bryant, Helen Christensen and Philip B Mitchell. 2017. Can Work Make You Mentally Ill? A Systematic Meta-Review of Work-Related Risk Factors for Common Mental Health Problems. Occupational and environmental medicine 74, 4, 301-310. https:\/\/doi.org\/10.1136\/oemed-2016-104015"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-61030-6_26"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2010.87"},{"key":"e_1_3_2_1_35_1","unstructured":"John Scott and Peter J Carrington. 2011. The Sage Handbook of Social Network Analysis. SAGE publications  John Scott and Peter J Carrington. 2011. The Sage Handbook of Social Network Analysis. SAGE publications"},{"key":"e_1_3_2_1_36_1","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. arXiv preprint arXiv:1609.02907. Retrieved from https:\/\/arxiv.org\/abs\/1609.02907  Thomas N Kipf and Max Welling. 2016. Semi-Supervised Classification with Graph Convolutional Networks. arXiv preprint arXiv:1609.02907. Retrieved from https:\/\/arxiv.org\/abs\/1609.02907"},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of Proceedings of the 31st International Conference on Neural Information Processing Systems. 1025-1035.","author":"Hamilton William L","unstructured":"William L Hamilton , Rex Ying and Jure Leskovec. Year. Inductive Representation Learning on Large Graphs . In Proceedings of Proceedings of the 31st International Conference on Neural Information Processing Systems. 1025-1035. William L Hamilton, Rex Ying and Jure Leskovec. Year. Inductive Representation Learning on Large Graphs. In Proceedings of Proceedings of the 31st International Conference on Neural Information Processing Systems. 1025-1035."},{"key":"e_1_3_2_1_38_1","volume-title":"Pietro Lio and Yoshua Bengio","author":"Veli\u010dkovi\u0107 Petar","year":"2017","unstructured":"Petar Veli\u010dkovi\u0107 , Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Lio and Yoshua Bengio . 2017 . Graph Attention Networks. arXiv preprint arXiv:1710.10903. Retrieved from https:\/\/arxiv.org\/abs\/1710.10903 Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio and Yoshua Bengio. 2017. Graph Attention Networks. arXiv preprint arXiv:1710.10903. Retrieved from https:\/\/arxiv.org\/abs\/1710.10903"},{"key":"e_1_3_2_1_39_1","volume-title":"Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980.","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980. Retrieved from https:\/\/arxiv.org\/abs\/1710.10903 Diederik P Kingma and Jimmy Ba. 2014. Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980. Retrieved from https:\/\/arxiv.org\/abs\/1710.10903"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3102399"},{"key":"e_1_3_2_1_41_1","unstructured":"CSIRO's Data61. 2018. Stellargraph Machine Learning Library. Github Repository. Retrieved from https:\/\/github.com\/stellargraph\/stellargraph  CSIRO's Data61. 2018. Stellargraph Machine Learning Library. Github Repository. Retrieved from https:\/\/github.com\/stellargraph\/stellargraph"},{"key":"e_1_3_2_1_42_1","volume-title":"Ron Weiss and Vincent Dubourg","author":"Pedregosa Fabian","year":"2011","unstructured":"Fabian Pedregosa , Ga\u00ebl Varoquaux , Alexandre Gramfort , Vincent Michel , Bertrand Thirion , Olivier Grisel , Mathieu Blondel , Peter Prettenhofer , Ron Weiss and Vincent Dubourg . 2011 . Scikit-Learn: Machine Learning in Python. the Journal of machine Learning research 12, 2825-2830. Fabian Pedregosa, Ga\u00ebl Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss and Vincent Dubourg. 2011. Scikit-Learn: Machine Learning in Python. the Journal of machine Learning research 12, 2825-2830."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Corinna Cortes and Vladimir Vapnik. 1995. Support-Vector Networks. Machine learning 20 3 273-297.  Corinna Cortes and Vladimir Vapnik. 1995. Support-Vector Networks. Machine learning 20 3 273-297.","DOI":"10.1007\/BF00994018"},{"key":"e_1_3_2_1_45_1","volume-title":"Rami Al-Rfou and Alex Alemi","author":"Abu-El-Haija Sami","year":"2017","unstructured":"Sami Abu-El-Haija , Bryan Perozzi , Rami Al-Rfou and Alex Alemi . 2017 . Watch Your Step: Learning Node Embeddings Via Graph Attention. arXiv preprint arXiv:1710.09599. Retrieved from https:\/\/arxiv.org\/abs\/1710.09599 Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou and Alex Alemi. 2017. Watch Your Step: Learning Node Embeddings Via Graph Attention. arXiv preprint arXiv:1710.09599. Retrieved from https:\/\/arxiv.org\/abs\/1710.09599"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btz418"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btaa501"},{"key":"e_1_3_2_1_48_1","volume-title":"Kim Esbensen and Paul Geladi","author":"Wold Svante","year":"1987","unstructured":"Svante Wold , Kim Esbensen and Paul Geladi . 1987 . Principal Component Analysis. Chemometrics and intelligent laboratory systems 2, 1-3, 37-52. Svante Wold, Kim Esbensen and Paul Geladi. 1987. Principal Component Analysis. Chemometrics and intelligent laboratory systems 2, 1-3, 37-52."},{"key":"e_1_3_2_1_49_1","volume-title":"Mohammad Ali Moni and Matloob Khushi","author":"Lu Haohui","year":"2021","unstructured":"Haohui Lu , Shahadat Uddin , Farshid Hajati , Mohammad Ali Moni and Matloob Khushi . 2021 . A Patient Network-Based Machine Learning Model for Disease Prediction: The Case of Type 2 Diabetes Mellitus. Applied Intelligence . http:\/\/dx.doi.org\/10.1007\/s10489-021-02533-w 10.1007\/s10489-021-02533-w Haohui Lu, Shahadat Uddin, Farshid Hajati, Mohammad Ali Moni and Matloob Khushi. 2021. A Patient Network-Based Machine Learning Model for Disease Prediction: The Case of Type 2 Diabetes Mellitus. Applied Intelligence. http:\/\/dx.doi.org\/10.1007\/s10489-021-02533-w"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Raimundo Real and Juan M Vargas. 1996. The Probabilistic Basis of Jaccard's Index of Similarity. Systematic biology 45 3 380-385.  Raimundo Real and Juan M Vargas. 1996. The Probabilistic Basis of Jaccard's Index of Similarity. Systematic biology 45 3 380-385.","DOI":"10.1093\/sysbio\/45.3.380"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1177\/1833358318769482"}],"event":{"name":"ACSW 2022: Australasian Computer Science Week 2022","location":"Brisbane Australia","acronym":"ACSW 2022"},"container-title":["Australasian Computer Science Week 2022"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511616.3513112","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3511616.3513112","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:11:47Z","timestamp":1750191107000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3511616.3513112"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,14]]},"references-count":51,"alternative-id":["10.1145\/3511616.3513112","10.1145\/3511616"],"URL":"https:\/\/doi.org\/10.1145\/3511616.3513112","relation":{},"subject":[],"published":{"date-parts":[[2022,2,14]]},"assertion":[{"value":"2022-03-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}