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1. Computer-Controlled 3D Freeform Surface Weaving

Author

Chen, Xiangjia, Lai, Lip M., Liu, Zishun, Dai, Chengkai, Leung, Isaac C. W., Wang, Charlie C. L., and Yam, Yeung

Subjects
Computer Science - Graphics, Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract

In this paper, we present a new computer-controlled weaving technology that enables the fabrication of woven structures in the shape of given 3D surfaces by using threads in non-traditional materials with high bending-stiffness, allowing for multiple applications with the resultant woven fabrics. A new weaving machine and a new manufacturing process are developed to realize the function of 3D surface weaving by the principle of short-row shaping. A computational solution is investigated to convert input 3D freeform surfaces into the corresponding weaving operations (indicated as W-code) to guide the operation of this system. A variety of examples using cotton threads, conductive threads and optical fibres are fabricated by our prototype system to demonstrate its functionality.

Published
2024

2. A Phenomenographic Approach on Teacher Conceptions of Teaching Artificial Intelligence (AI) in K-12 Schools

Author

Yau, King Woon, CHAI, C. S., Chiu, Thomas K. F., Meng, Helen, King, Irwin, and Yam, Yeung

Abstract

Artificial intelligence (AI) education for K-12 students is an emerging necessity, owing to the rapid advancement and deployment of AI technologies. It is essential to take teachers' perspectives into account when creating ecologically valid AI education programmes for K-12 settings. However, very few studies investigated teacher perception of AI education. Phenomenography is an empirical research method that was widely used to understand teacher's interpretive understanding of new phenomenon, in this study, the teaching of AI in secondary school. Therefore, the present study investigated teachers' conceptions of teaching AI using a phenomenographic approach. Twenty-eight in-service teachers from 17 secondary schools in Hong Kong were invited to participate in an interview after implementing an AI curriculum. Six categories of teacher conceptions were identified: (1) technology bridging, (2) knowledge delivery, (3) interest stimulation, (4) ethics establishment, (5) capability cultivation, and (6) intellectual development. The hierarchical relationships of the six concepts were organised as an outcome space. The space shows a range of surface to deep conceptions and offers an understanding of how teachers perceive AI education through their teaching experience. Two learning paths have been suggested for cultivating technical and non-technical teachers for teaching AI. These learning paths provide insights for teacher educators and policymakers to enhance teachers' competence in teaching AI and promote general AI education for K-12 students.

Published
2023
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5. Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI) Curriculum

Author

Chiu, Thomas K. F., Meng, Helen, Chai, Ching-Sing, King, Irwin, Wong, Savio, and Yam, Yeung

Subjects
Computer Science - Artificial Intelligence
Abstract

Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education and evaluated its efficacy. While AI is conventionally taught in tertiary level education, our co-creation process successfully developed the curriculum that has been used in secondary school teaching in Hong Kong and received positive feedback. Background: AI4Future is a cross-sector project that engages five major partners - CUHK Faculty of Engineering and Faculty of Education, Hong Kong secondary schools, the government and the AI industry. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. This team formation bridges the gap between researchers in engineering and education, together with practitioners in education context. Research Questions: What are the main features of the curriculum content developed through the co-creation process? Would the curriculum significantly improve the students perceived competence in, as well as attitude and motivation towards AI? What are the teachers perceptions of the co-creation process that aims to accommodate and foster teacher autonomy? Methodology: This study adopted a mix of quantitative and qualitative methods and involved 335 student participants. Findings: 1) two main features of learning resources, 2) the students perceived greater competence, and developed more positive attitude to learn AI, and 3) the co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms., Comment: 8 pages 5 figures

Published
2021

6. Imitation Learning from Expert Video Data for Dissection Trajectory Prediction in Endoscopic Surgical Procedure

Author

Li, Jianan, Jin, Yueming, Chen, Yueyao, Yip, Hon-Chi, Scheppach, Markus, Chiu, Philip Wai-Yan, Yam, Yeung, Meng, Helen Mei-Ling, Dou, Qi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Greenspan, Hayit, editor, Madabhushi, Anant, editor, Mousavi, Parvin, editor, Salcudean, Septimiu, editor, Duncan, James, editor, Syeda-Mahmood, Tanveer, editor, and Taylor, Russell, editor

Published
2023
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9. Creation and Evaluation of a Pretertiary Artificial Intelligence (AI) Curriculum

Author

Chiu, Thomas K. F., Meng, Helen, Chai, Ching-Sing, King, Irwin, Wong, Savio, and Yam, Yeung

Abstract

Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created the first pretertiary AI curriculum at the secondary school level for Hong Kong and evaluated its efficacy. This study added to the AI education community by introducing a new AI curriculum framework. The preposttest multifactors evaluation about students' perceptions of AI learning confirmed that the curriculum is effective in promoting AI learning. The teachers also confirmed the co-creation process enhanced their capacity to implement AI education. Background: AI4Future is a cross-sector project that engages five major partners--CUHK's Faculty of Engineering and Faculty of Education, secondary schools, Hong Kong government, and AI industry. A team of 14 professors collaborated with 17 principals and teachers from six secondary schools to co-create the curriculum. Research Questions: Would the curriculum significantly improve the student perceived competence, attitude, and motivation toward AI learning? How does the co-creation process benefit the implementation of the curriculum? Methodology: The participants were 335 students and eight teachers from the secondary schools. This study adopted a mix-method with quantitative data measures at pre- and post-questionnaires and qualitative data emphasizes teachers' perspectives on the co-creation process. Paired t-tests and ANCOVAs, and thematic analysis were used to analyze the data. Findings: (1) students perceived greater competence and developed a more positive attitude to learn AI; and (2) the co-creation process enhanced teachers' knowledge in AI, as well as fostered teachers' autonomy in bringing the subject matter into their classrooms.

Published
2022
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10. Evaluating assumptions of scales for subjective assessment of thermal environments – Do laypersons perceive them the way, we researchers believe?

Author

Schweiker, Marcel, André, Maíra, Al-Atrash, Farah, Al-Khatri, Hanan, Alprianti, Rea Risky, Alsaad, Hayder, Amin, Rucha, Ampatzi, Eleni, Arsano, Alpha Yacob, Azar, Elie, Bannazadeh, Bahareh, Batagarawa, Amina, Becker, Susanne, Buonocore, Carolina, Cao, Bin, Choi, Joon-Ho, Chun, Chungyoon, Daanen, Hein, Damiati, Siti Aisyah, Daniel, Lyrian, De Vecchi, Renata, Dhaka, Shivraj, Domínguez-Amarillo, Samuel, Dudkiewicz, Edyta, Edappilly, Lakshmi Prabha, Fernández-Agüera, Jesica, Folkerts, Mireille, Frijns, Arjan, Gaona, Gabriel, Garg, Vishal, Gauthier, Stephanie, Jabbari, Shahla Ghaffari, Harimi, Djamila, Hellwig, Runa T, Huebner, Gesche M, Jin, Quan, Jowkar, Mina, Kim, Jungsoo, King, Nelson, Kingma, Boris, Koerniawan, M Donny, Kolarik, Jakub, Kumar, Shailendra, Kwok, Alison, Lamberts, Roberto, Laska, Marta, Lee, MC Jeffrey, Lee, Yoonhee, Lindermayr, Vanessa, Mahaki, Mohammadbagher, Marcel-Okafor, Udochukwu, Marín-Restrepo, Laura, Marquardsen, Anna, Martellotta, Francesco, Mathur, Jyotirmay, Mino-Rodriguez, Isabel, Montazami, Azadeh, Mou, Di, Moujalled, Bassam, Nakajima, Mia, Ng, Edward, Okafor, Marcellinus, Olweny, Mark, Ouyang, Wanlu, de Abreu, Ana Lígia Papst, Pérez-Fargallo, Alexis, Rajapaksha, Indrika, Ramos, Greici, Rashid, Saif, Reinhart, Christoph F, Rivera, Ma Isabel, Salmanzadeh, Mazyar, Schakib-Ekbatan, Karin, Schiavon, Stefano, Shooshtarian, Salman, Shukuya, Masanori, Soebarto, Veronica, Suhendri, Suhendri, Tahsildoost, Mohammad, Tartarini, Federico, Teli, Despoina, Tewari, Priyam, Thapa, Samar, Trebilcock, Maureen, Trojan, Jörg, Tukur, Ruqayyatu B, Voelker, Conrad, Yam, Yeung, Yang, Liu, Zapata-Lancaster, Gabriela, Zhai, Yongchao, Zhu, Yingxin, and Zomorodian, ZahraSadat

Subjects
Thermal comfort, Thermal sensation, Thermal acceptance, Field study, Scales, Post-Occupancy-Evaluation: Climatic zone, Season, Language, Adaptation, Diversity, Engineering, Built Environment and Design, Building & Construction
Abstract

People's subjective response to any thermal environment is commonly investigated by using rating scales describing the degree of thermal sensation, comfort, and acceptability. Subsequent analyses of results collected in this way rely on the assumption that specific distances between verbal anchors placed on the scale exist and that relationships between verbal anchors from different dimensions that are assessed (e.g. thermal sensation and comfort) do not change. Another inherent assumption is that such scales are independent of the context in which they are used (climate zone, season, etc.). Despite their use worldwide, there is indication that contextual differences influence the way the scales are perceived and therefore question the reliability of the scales’ interpretation. To address this issue, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires. Results, analysed by means of robust statistical techniques, revealed that only a subset of the responses are in accordance with the mentioned assumptions. Significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales. It was also found that respondents’ interpretations of scales changed with contextual factors, such as climate, season, and language. These findings highlight the need to carefully consider context-dependent factors in interpreting and reporting results from thermal comfort studies or post-occupancy evaluations, as well as to revisit the use of rating scales and the analysis methods used in thermal comfort studies to improve their reliability.

Published
2020

11. Publisher Correction: The Scales Project, a cross-national dataset on the interpretation of thermal perception scales.

Author

Schweiker, Marcel, Abdul-Zahra, Amar, André, Maíra, Al-Atrash, Farah, Al-Khatri, Hanan, Alprianti, Rea, Alsaad, Hayder, Amin, Rucha, Ampatzi, Eleni, Arsano, Alpha, Azadeh, Montazami, Azar, Elie, Bahareh, Bannazadeh, Batagarawa, Amina, Becker, Susanne, Buonocore, Carolina, Cao, Bin, Choi, Joon-Ho, Chun, Chungyoon, Daanen, Hein, Damiati, Siti, Daniel, Lyrian, Vecchi, Renata, Dhaka, Shivraj, Domínguez-Amarillo, Samuel, Dudkiewicz, Edyta, Edappilly, Lakshmi, Fernández-Agüera, Jesica, Folkerts, Mireille, Frijns, Arjan, Gaona, Gabriel, Garg, Vishal, Gauthier, Stephanie, Jabbari, Shahla, Harimi, Djamila, Hellwig, Runa, Huebner, Gesche, Jin, Quan, Jowkar, Mina, Kania, Renate, Kim, Jungsoo, King, Nelson, Kingma, Boris, Koerniawan, M, Kolarik, Jakub, Kumar, Shailendra, Kwok, Alison, Lamberts, Roberto, Laska, Marta, Lee, M, Lee, Yoonhee, Lindermayr, Vanessa, Mahaki, Mohammadbagher, Marcel-Okafor, Udochukwu, Marín-Restrepo, Laura, Marquardsen, Anna, Martellotta, Francesco, Mathur, Jyotirmay, McGill, Gráinne, Mino-Rodriguez, Isabel, Mou, Di, Moujalled, Bassam, Nakajima, Mia, Ng, Edward, Okafor, Marcellinus, Olweny, Mark, Ouyang, Wanlu, Papst de Abreu, Ana, Pérez-Fargallo, Alexis, Rajapaksha, Indrika, Ramos, Greici, Rashid, Saif, Reinhart, Christoph, Rivera, Ma, Salmanzadeh, Mazyar, Schakib-Ekbatan, Karin, Schiavon, Stefano, Shooshtarian, Salman, Shukuya, Masanori, Soebarto, Veronica, Tahsildoost, Mohammad, Tartarini, Federico, Teli, Despoina, Tewari, Priyam, Thapa, Samar, Trebilcock, Maureen, Trojan, Jörg, Tukur, Ruqayyatu, Voelker, Conrad, Yam, Yeung, Yang, Liu, Zapata-Lancaster, Gabriela, Zhai, Yongchao, Zhu, Yingxin, and Zomorodian, Zahra

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2020

13. The Scales Project, a cross-national dataset on the interpretation of thermal perception scales.

Author

Schweiker, Marcel, Abdul-Zahra, Amar, André, Maíra, Al-Atrash, Farah, Al-Khatri, Hanan, Alprianti, Rea, Alsaad, Hayder, Amin, Rucha, Ampatzi, Eleni, Arsano, Alpha, Azadeh, Montazami, Azar, Elie, Bahareh, Bannazadeh, Batagarawa, Amina, Becker, Susanne, Buonocore, Carolina, Cao, Bin, Choi, Joon-Ho, Chun, Chungyoon, Daanen, Hein, Damiati, Siti, Daniel, Lyrian, Vecchi, Renata, Dhaka, Shivraj, Domínguez-Amarillo, Samuel, Dudkiewicz, Edyta, Edappilly, Lakshmi, Fernández-Agüera, Jesica, Folkerts, Mireille, Frijns, Arjan, Gaona, Gabriel, Garg, Vishal, Gauthier, Stephanie, Jabbari, Shahla, Harimi, Djamila, Hellwig, Runa, Huebner, Gesche, Jin, Quan, Jowkar, Mina, Kania, Renate, Kim, Jungsoo, King, Nelson, Kingma, Boris, Koerniawan, M, Kolarik, Jakub, Kumar, Shailendra, Kwok, Alison, Lamberts, Roberto, Laska, Marta, Lee, M, Lee, Yoonhee, Lindermayr, Vanessa, Mahaki, Mohammadbagher, Marcel-Okafor, Udochukwu, Marín-Restrepo, Laura, Marquardsen, Anna, Martellotta, Francesco, Mathur, Jyotirmay, McGill, Gráinne, Mino-Rodriguez, Isabel, Mou, Di, Moujalled, Bassam, Nakajima, Mia, Ng, Edward, Okafor, Marcellinus, Olweny, Mark, Ouyang, Wanlu, Papst de Abreu, Ana, Pérez-Fargallo, Alexis, Rajapaksha, Indrika, Ramos, Greici, Rashid, Saif, Reinhart, Christoph, Rivera, Ma, Salmanzadeh, Mazyar, Schakib-Ekbatan, Karin, Schiavon, Stefano, Shooshtarian, Salman, Shukuya, Masanori, Soebarto, Veronica, Tahsildoost, Mohammad, Tartarini, Federico, Teli, Despoina, Tewari, Priyam, Thapa, Samar, Trebilcock, Maureen, Trojan, Jörg, Tukur, Ruqayyatu, Voelker, Conrad, Yam, Yeung, Yang, Liu, Zapata-Lancaster, Gabriela, Zhai, Yongchao, Zhu, Yingxin, and Zomorodian, Zahra

Abstract

Thermal discomfort is one of the main triggers for occupants interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses.

Published
2019

14. Prognostic value of age adjusted segment involvement score as measured by coronary computed tomography: a potential marker of vascular age

Author

Ayoub, Chadi, Kritharides, Leonard, Yam, Yeung, Chen, Li, Hossain, Alomgir, Achenbach, Stephan, Al-Mallah, Mouaz H, Andreini, Daniele, Berman, Daniel S, Budoff, Matthew J, Cademartiri, Filippo, Callister, Tracy Q, Chang, Hyuk-Jae, Chinnaiyan, Kavitha, Cury, Ricardo C, Delago, Augustin, Dunning, Allison, Feuchtner, Gudrun, Gomez, Millie, Gransar, Heidi, Hadamitzky, Martin, Hausleiter, Joerg, Hindoyan, Niree, Kaufmann, Philipp A, Kim, Yong-Jin, Leipsic, Jonathon, Maffei, Erica, Marques, Hugo, Pontone, Gianluca, Raff, Gilbert, Rubinshtein, Ronen, Shaw, Leslee J, Villines, Todd C, Min, James K, and Chow, Benjamin JW

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease, Clinical Research, Biomedical Imaging, Cardiovascular, Atherosclerosis, Aging, Heart Disease - Coronary Heart Disease, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Good Health and Well Being, Age Factors, Aged, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Female, Follow-Up Studies, Humans, Male, Middle Aged, Plaque, Atherosclerotic, Predictive Value of Tests, Prognosis, Prospective Studies, Registries, Risk Factors, Time Factors, Coronary, Computed tomography, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

Extent of coronary atherosclerotic disease (CAD) burden on coronary computed tomography angiography (CCTA) as measured by segment involvement score (SIS) has a prognostic value. We sought to investigate the incremental prognostic value of 'age adjusted SIS' (aSIS), which may be a marker of premature atherosclerosis and vascular age. Consecutive patients were prospectively enrolled into the CONFIRM (Coronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicentre) multinational observational study. Patients were followed for the outcome of all-cause death. aSIS was calculated on CCTA for each patient, and its incremental prognostic value was evaluated. A total of 22,211 patients [mean age 58.5 ± 12.7 years, 55.8% male) with a median follow-up of 27.3 months (IQR 17.8, 35.4)] were identified. After adjustment for clinical factors and presence of obstructive CAD, higher aSIS was associated with increased death on multivariable analysis, with hazard ratio (HR) 2.40 (1.83-3.16, p

Published
2018

19. A Clinical Model to Identify Patients With High-Risk Coronary Artery Disease

Author

Yang, Yelin, Chen, Li, Yam, Yeung, Achenbach, Stephan, Al-Mallah, Mouaz, Berman, Daniel S, Budoff, Matthew J, Cademartiri, Filippo, Callister, Tracy Q, Chang, Hyuk-Jae, Cheng, Victor Y, Chinnaiyan, Kavitha, Cury, Ricardo, Delago, Augustin, Dunning, Allison, Feuchtner, Gudrun, Hadamitzky, Martin, Hausleiter, Jörg, Karlsberg, Ronald P, Kaufmann, Philipp A, Kim, Yong-Jin, Leipsic, Jonathon, LaBounty, Troy, Lin, Fay, Maffei, Erica, Raff, Gilbert L, Shaw, Leslee J, Villines, Todd C, Min, James K, and Chow, Benjamin JW

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, Atherosclerosis, Prevention, Heart Disease, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Aged, Coronary Angiography, Coronary Artery Disease, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Registries, Retrospective Studies, Risk Assessment, Risk Factors, Tomography, X-Ray Computed, computed tomographic coronary angiography, high-risk coronary artery disease, risk factors, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThis study sought to develop a clinical model that identifies patients with and without high-risk coronary artery disease (CAD).BackgroundAlthough current clinical models help to estimate a patient's pre-test probability of obstructive CAD, they do not accurately identify those patients with and without high-risk coronary anatomy.MethodsRetrospective analysis of a prospectively collected multinational coronary computed tomographic angiography (CTA) cohort was conducted. High-risk anatomy was defined as left main diameter stenosis ≥50%, 3-vessel disease with diameter stenosis ≥70%, or 2-vessel disease involving the proximal left anterior descending artery. Using a cohort of 27,125, patients with a history of CAD, cardiac transplantation, and congenital heart disease were excluded. The model was derived from 24,251 consecutive patients in the derivation cohort and an additional 7,333 nonoverlapping patients in the validation cohort.ResultsThe risk score consisted of 9 variables: age, sex, diabetes, hypertension, current smoking, hyperlipidemia, family history of CAD, history of peripheral vascular disease, and chest pain symptoms. Patients were divided into 3 risk categories: low (≤7 points), intermediate (8 to 17 points) and high (≥18 points). The model was statistically robust with area under the curve of 0.76 (95% confidence interval [CI]: 0.75 to 0.78) in the derivation cohort and 0.71 (95% CI: 0.69 to 0.74) in the validation cohort. Patients who scored ≤7 points had a low negative likelihood ratio (

Published
2015

20. Prognostic and Therapeutic Implications of Statin and Aspirin Therapy in Individuals With Nonobstructive Coronary Artery Disease

Author

Chow, Benjamin JW, Small, Gary, Yam, Yeung, Chen, Li, McPherson, Ruth, Achenbach, Stephan, Al-Mallah, Mouaz, Berman, Daniel S, Budoff, Matthew J, Cademartiri, Filippo, Callister, Tracy Q, Chang, Hyuk-Jae, Cheng, Victor Y, Chinnaiyan, Kavitha, Cury, Ricardo, Delago, Augustin, Dunning, Allison, Feuchtner, Gundrun, Hadamitzky, Martin, Hausleiter, Jörg, Karlsberg, Ronald P, Kaufmann, Philipp A, Kim, Yong-Jin, Leipsic, Jonathon, LaBounty, Troy, Lin, Fay, Maffei, Erica, Raff, Gilbert L, Shaw, Leslee J, Villines, Todd C, and Min, James K

Subjects
Patient Safety, Cardiovascular, Heart Disease, Atherosclerosis, Clinical Research, Heart Disease - Coronary Heart Disease, Evaluation of treatments and therapeutic interventions, Detection, screening and diagnosis, 6.1 Pharmaceuticals, 4.2 Evaluation of markers and technologies, Good Health and Well Being, Adult, Aged, Asia, Aspirin, Canada, Coronary Angiography, Coronary Artery Disease, Coronary Stenosis, Europe, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Kaplan-Meier Estimate, Male, Middle Aged, Multivariate Analysis, Odds Ratio, Platelet Aggregation Inhibitors, Predictive Value of Tests, Primary Prevention, Proportional Hazards Models, Prospective Studies, Protective Factors, Registries, Risk Factors, Severity of Illness Index, Time Factors, Tomography, X-Ray Computed, Treatment Outcome, United States, aspirin, coronary angiography, coronary atherosclerosis, mortality, prognosis, statin, CONFIRM Investigators, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

ObjectiveWe sought to examine the risk of mortality associated with nonobstructive coronary artery disease (CAD) and to determine the impact of baseline statin and aspirin use on mortality.Approach and resultsCoronary computed tomographic angiography permits direct visualization of nonobstructive CAD. To date, the prognostic implications of nonobstructive CAD and the potential benefit of directing therapy based on nonobstructive CAD have not been carefully examined. A total of 27 125 consecutive patients who underwent computed tomographic angiography (12 enrolling centers and 6 countries) were prospectively entered into the COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter (CONFIRM) registry. Patients, without history of previous CAD or obstructive CAD, for whom baseline statin and aspirin use was available were analyzed. Each coronary segment was classified as normal or nonobstructive CAD (1%-49% stenosis). Patients were followed up for a median of 27.2 months for all-cause mortality. The study comprised 10 418 patients (5712 normal and 4706 with nonobstructive CAD). In multivariable analyses, patients with nonobstructive CAD had a 6% (95% confidence interval, 1%-12%) higher risk of mortality for each additional segment with nonobstructive plaque (P=0.021). Baseline statin use was associated with a reduced risk of mortality (hazard ratio, 0.44; 95% confidence interval, 0.28-0.68; P=0.0003), a benefit that was present for individuals with nonobstructive CAD (hazard ratio, 0.32; 95% confidence interval, 0.19-0.55; P

Published
2015

25. List of Contributors

Author

Abbott, Jake J., primary, Abedin-Nasab, Mohammad H., additional, Abiri, Ahmad, additional, Afshari, Elnaz, additional, Alamdar, Alireza, additional, Alazmani, Ali, additional, Anderson, Oliver, additional, Andres, Axel, additional, Antico, Maria, additional, Arulampalam, Tan, additional, Azizian, Mahdi, additional, Bergeles, Christos, additional, Bergman, Per, additional, Bisley, James, additional, Blacker, Steven J., additional, Boni, Andrea, additional, Buchs, Nicolas Christian, additional, Cengiz, Turgut Bora, additional, Chan, Danny Tat-Ming, additional, Chiu, Philip Wai Yan, additional, Choi, Hyouk Ryeol, additional, Chudy, Darko, additional, Cochetti, Giovanni, additional, Crawford, Ross, additional, Cross, William, additional, Culmer, Peter, additional, Daimios, Simon, additional, De Mathelin, Michel, additional, De Momi, Elena, additional, De Vermandois, Jacopo Adolfo Rossi, additional, Dlaka, Domagoj, additional, Dooley, John R., additional, Drobilo, Luka, additional, Dutson, Erik, additional, Erchinger, Thomas, additional, Fan, Zhencheng, additional, Fanson, Richard, additional, Farahmand, Farzam, additional, Faraji-Dana, Zahra, additional, Faridpooya, Koorosh, additional, Fernando, Anthony, additional, Fontanarosa, Davide, additional, Gan, Chee Wee, additional, Garayt, Mathieu, additional, Gaudio, Gianluca, additional, Gorgun, Emre, additional, Gould, Jon C., additional, Groenhuis, Vincent, additional, Grundfest, Warren, additional, Guo, Ziyan, additional, Gupta, Anjuli M., additional, Hagen, Monika, additional, Higgins, Rana M., additional, Hladio, Andre, additional, Hobeika, Joe, additional, Iordachita, Iulian, additional, Jaiprakash, Anjali, additional, Jaramaz, Branislav, additional, Jayne, David, additional, Jerbić, Bojan, additional, Jinnah, Alexander H., additional, Jinnah, Riyaz H., additional, Johnson, Kelly R., additional, Jonmohamadi, Yaqub, additional, Juo, Yen-Yi, additional, Kajtazi, Marin, additional, Kang, Jin U., additional, Keggi, John M., additional, Khalaji, Iman, additional, Kilby, Warren, additional, Kim, Uikyum, additional, Kim, Yong Bum, additional, Konan, Sujith, additional, Kottenstette, Nicholas, additional, Kwok, Ka-Wai, additional, Lau, Ka Chun, additional, Lawrence, Jeffrey M., additional, Leong, Martin Chun-Wing, additional, Leung, Michael K.K., additional, Leung, Yun Yee, additional, Li, Changsheng, additional, Liang, Wenyu, additional, Liao, Hongen, additional, Liao, Zhuxiu, additional, Lim, Chwee Ming, additional, Lim, Hsueh Yee, additional, Liu, May, additional, Ma, Longfei, additional, Maden, Carla, additional, Maggitti, Michael J., additional, Mariampillai, Adrian L.D., additional, Mattos, Leonardo S., additional, Maurer, Calvin R., additional, Mearini, Ettore, additional, Milas, Jamie, additional, Mirbagheri, Alireza, additional, Mitra, Riddhit, additional, Moccia, Sara, additional, Moradi, Mehdi, additional, Morel, Philippe, additional, Moustris, George, additional, Muir, Jeffrey, additional, Mushtaq, Faisal, additional, Nageotte, Florent, additional, Nasseri, M. Ali, additional, Nathan, Mohan, additional, Naylor, Michael, additional, Ndubizu, Gordian U., additional, Ng, Cailin, additional, Oh, Daniel, additional, Ohmura, Yasushi, additional, Oriot, Elena, additional, Pandey, Ajay K., additional, Pappas, Theodore, additional, Peloso, Andrea, additional, Pensa, Jake, additional, Penza, Veronica, additional, Plaskos, Christopher, additional, Poon, Wai-Sang, additional, Protyniak, Bogdan, additional, Qiu, Liang, additional, Razjigaev, Andrew, additional, Ren, Hongliang, additional, Riviere, Cameron N., additional, Roberts, Jonathan, additional, Russo, Sheila, additional, Saber, Omid, additional, Saeedi-Hosseiny, Marzieh S., additional, Saragaglia, Dominique, additional, Sarkar, Saeed, additional, Sasazawa, Fumio, additional, Sayeh, Sohail, additional, Šekoranja, Bojan, additional, Sellers, William J., additional, Seok, Dong-Yeop, additional, Shalhoub, Sami, additional, Siepel, Françoise J., additional, Sokhanvar, Saeed, additional, Sorger, Jonathan, additional, Standish, Beau A., additional, Steele, Scott R., additional, Stiperski, Ivan, additional, Stramigioli, Stefano, additional, Strydom, Mario, additional, Su, Hao, additional, Šuligoj, Filip, additional, Sun, Songping, additional, Švaco, Marko, additional, Sznitman, Raphael, additional, Takahashi, Masahiro, additional, Tan, Kok Kiong, additional, Tao, Anna, additional, Todorov, Alex, additional, Toso, Christian, additional, Turco, Morena, additional, Turković, Marija, additional, Tzafestas, Costas, additional, Vander Poorten, Emmanuel, additional, Vidaković, Josip, additional, Vitez, Nikola, additional, Volpin, Andrea, additional, Wu, Liao, additional, Yam, Yeung, additional, Yang, Victor X.D., additional, Zanne, Philippe, additional, Žgaljić, Adrian, additional, Zhang, Xinran, additional, Zorn, Lucile, additional, and Župančić, Ivan, additional

Published
2020
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33. A Novel User-Specific Wearable Controller for Surgical Robots

Author

Poon, Carmen C. Y., Leung, Esther Y. Y., Lau, Ka Chun, Leung, Billy H. K., Zheng, Yali L., Chiu, Philip W. Y., Yam, Yeung, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, and Marcus, Aaron, editor

Published
2015
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34. Prognostic value of vasodilator response using rubidium-82 positron emission tomography myocardial perfusion imaging in patients with coronary artery disease

Author

Arasaratnam, Punitha, Sadreddini, Masoud, Yam, Yeung, Kansal, Vinay, Dorbala, Sharmila, Di Carli, Marcelo F., Beanlands, Rob S., Merhige, Michael E., Williams, Brent A., Veledar, Emir, Min, James K., Chen, Li, Ruddy, Terrence D., Germano, Guido, Berman, Daniel S., Shaw, Leslee J., and Chow, Benjamin J. W.

Published
2018
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35. Curriculum Design of Artificial Intelligence and Sustainability in Secondary School

Author

Cai, Jinyi, Kwan, Mei-Po, Hou, Chunyu, Liu, Dong, Yam, Yeung, Cai, Jinyi, Kwan, Mei-Po, Hou, Chunyu, Liu, Dong, and Yam, Yeung

Abstract

Artificial Intelligence is revolutionizing numerous sectors with its transformative power, while at the same time, there is an increasing sense of urgency to address sustainability challenges. Despite the significance of both areas, secondary school curriculums still lack comprehensive integration of AI and sustainability education. This paper presents a curriculum designed to bridge this gap. The curriculum integrates progressive objectives, computational thinking competencies and system thinking components across five modules—awareness, knowledge, interaction, empowerment and ethics—to cater to varying learner levels. System thinking components help students understand sustainability in a holistic manner. Computational thinking competencies aim to cultivate computational thinkers to guide the design of curriculum activities.

Published
2023

41. Predictive Value of Cardiac Computed Tomography and the Impact of Renal Function on All Cause Mortality (from Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes)

Author

Dwivedi, Girish, Cocker, Myra, Yam, Yeung, Achenbach, Stephan, Al-Mallah, Mouaz, Berman, Daniel S., Budoff, Matthew J., Cademartiri, Filippo, Callister, Tracy Q., Chang, Hyuk-Jae, Cheng, Victor, Chinnaiyan, Kavitha M., Delago, Augustin, Dunning, Allison M., Hadamitzky, Martin, Hausleiter, Jörg, Kaufmann, Philipp A., LaBounty, Troy M., Lin, Fay, Maffei, Erica, Raff, Gilbert L., Shaw, Leslee J., Villines, Todd C., Min, James K., and Chow, Benjamin J.W.

Published
2013
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