ORCID Profile
0000-0002-8199-2122
Current Organisations
Universiti Putra Malaysia
,
Kent State University
,
Università Vita Salute San Raffaele
,
University of Gloucestershire
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Publications
Sustainability performance assessment using self-organizing maps (SOM) and classification and ensembles of regression trees (CART)
Publisher: MDPI AG
Date: 31-03-2021
DOI: 10.3390/SU13073870
Abstract: This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than in idual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment.
The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2016
EAU-EANM-ESTRO-ESUR-SIOG Prostate Cancer Guideline Panel Consensus Statements for Deferred Treatment with Curative Intent for Localised Prostate Cancer from an International Collaborative Study (DETEC
Publisher: Elsevier BV
Date: 12-2019
DOI: 10.1016/J.EURURO.2019.09.020
Abstract: There is uncertainty in deferred active treatment (DAT) programmes, regarding patient selection, follow-up and monitoring, reclassification, and which outcome measures should be prioritised. To develop consensus statements for all domains of DAT. A protocol-driven, three phase study was undertaken by the European Association of Urology (EAU)-European Association of Nuclear Medicine (EANM)-European Society for Radiotherapy and Oncology (ESTRO)-European Association of Urology Section of Urological Research (ESUR)-International Society of Geriatric Oncology (SIOG) Prostate Cancer Guideline Panel in conjunction with partner organisations, including the following: (1) a systematic review to describe heterogeneity across all domains (2) a two-round Delphi survey involving a large, international panel of stakeholders, including healthcare practitioners (HCPs) and patients and (3) a consensus group meeting attended by stakeholder group representatives. Robust methods regarding what constituted the consensus were strictly followed. A total of 109 HCPs and 16 patients completed both survey rounds. Of 129 statements in the survey, consensus was achieved in 66 (51%) the rest of the statements were discussed and voted on in the consensus meeting by 32 HCPs and three patients, where consensus was achieved in additional 27 statements (43%). Overall, 93 statements (72%) achieved consensus in the project. Some uncertainties remained regarding clinically important thresholds for disease extent on biopsy in low-risk disease, and the role of multiparametric magnetic resonance imaging in determining disease stage and aggressiveness as a criterion for inclusion and exclusion. Consensus statements and the findings are expected to guide and inform routine clinical practice and research, until higher levels of evidence emerge through prospective comparative studies and clinical trials. We undertook a project aimed at standardising the elements of practice in active surveillance programmes for early localised prostate cancer because currently there is great variation and uncertainty regarding how best to conduct them. The project involved large numbers of healthcare practitioners and patients using a survey and face-to-face meeting, in order to achieve agreement (ie, consensus) regarding best practice, which will provide guidance to clinicians and researchers.
Related Organisations
University Of Gloucestershire
Location: United Kingdom of Great Britain and Northern Ireland
Related Funding Activities
No related grants have been discovered for Shahla Asadi.