7,979 research outputs found
Author Interview with Brian D. Anderson
No full textBrian D. Anderson was our feature artist of the week, October 19th - 23rd, 2020.https://jagworks.southalabama.edu/vid_presentations/1010/thumbnail.jp
Editorial: Explainable artificial intelligence models and methods in finance and healthcare
No full textThis article is a foreword to a special issue on "Explainable artificial intelligence models and methods in finance and healthcare" and introduces the main articles of the collection. The core topic of this special issue is explainability and trusting algorithmic output
Explainable Artificial Intelligence models and methods in Finance and Healthcare
No full textIn the last years, the fast and growing data availability has allowed providing highly predictive responses for the advanced research fields. Sophisticated machine learning models and techniques were then developed together with artificial intelligence-based systems. Increasing attention is given to Artificial Intelligence (AI), especially due to its algorithms, which give rise to robust predictions. Nevertheless, AI systems have a black box nature resulting in automated decision-making. This can classify a user into a category associated with the prediction of the individual behavior without specifying the underlying rationale. Some concerns about the adequacy of the AI models and methods in regulatory scenarios arise, primarily due to the possible biases generated by the Machine Learning algorithms. This leads organizations to claim high credibility and interpretability to provide effective operational control. The lack of transparency and explainability is, therefore, a critical point for policymakers and regulators aimed at avoiding wrong actions with adverse consequences on society. This issue is more evident in the financial and banking sectors, where the use cases of AI extend to the contexts of risk management, predictive analytics, and fraud detection, as well as in the healthcare field, where the focus is on both the funding management process of the healthcare services and the improvement of the diagnostic precision. We can resort to AI-based systems to predict the financial, default, funding loss, and diagnostic-related risks. However, AI-based systems require that the main criteria, which support the predictions, are known in order to assess the related severity and foster the appropriate measures to reduce the risks in case of shocks in the financial systems, changes in market conditions, or monitoring of the healthcare policies. For the purpose of explaining and interpreting machine learning models, eXplainable Artificial Intelligence (XAI) represents a fundamental field for understanding the steps and methods driving the decision process. In line with the policy requirements of transparency, this Research Topic aims to include original papers proposing the development of innovative XAI methodologies for global or local explanations in the research area of: • the financial and banking sectors - mainly focused on credit scoring, which involves lending algorithms, price discovery (representing the basis of financial robot advisory algorithms), and cyber risk management (greatly critical due to the increasingly online connections); • the healthcare field mainly focused on the evaluation of the funding and management policies
Competition policy. by Brian Ellis
No full texttag=1 data=Competition policy. by Brian Ellis
tag=2 data=Ellis, Brian
tag=3 data=Australian Rationalist,
tag=5 data=46
tag=6 data=Autumn/Winter 1998
tag=7 data=51-56.
tag=8 data=ECONOMIC CONDITIONS
tag=9 data=COMPETITION%CORPORATISATION%NATIONAL COMPETITION POLICY%PRIVATE SECTOR PUBLIC SECTOR EFFECTIVENESS%SERVICE DELIVERY%SOCIAL POLICY%INNOVATION
tag=10 data=Examines the Government's National Competition Policy in relation to encouraging R&D, and the corporisation of public services and utilites. The author is Emeritus Professor of Philosophy at La Trobe UNiversity and Vice-President of the Rationalist Society of Australia. Article Taken from What's New.
tag=13 data=CABExamines the Government's National Competition Policy in relation to encouraging R&D, and the corporisation of public services and utilites. The author is Emeritus Professor of Philosophy at La Trobe UNiversity and Vice-President of the Rationalist Society of Australia. Article Taken from What's New
Art Behind Gaming: Brian D. Anderson
No full textA discussion with author Brian D. Anderson about worldbuilding in fantasy. Part of the Art Behind Gaming Online Con.https://jagworks.southalabama.edu/vid_presentations/1046/thumbnail.jp
In Honour of Brian MacWhinney: A Personal Account
No full textWhile this volume and the writings have made it amply clear what significant contributions Professor Brian MacWhinney has made to the field at large, in this afterword, we begin with a senior member of our author team (Ping Li, PL) followed by a mid-career member (Helen Zhao, HZ) and an early career member (Zhe Gao, ZG), to provide our personal accounts of Brian not only as a leading scholar but also as a role model who touches and changes people’s lives
Interview with Brian Alleyne, Sociologist Studying KDE
No full textA few months ago, the British journal Sociology published an article titled "Challenging Code: A Sociological Reading of the KDE Free Software Project". Eager to find out what a 'sociological reading' of KDE entails, Dot editor Oriol Mirosa rushed to contact the article's author, sociologist Brian Alleyne, who graciously and patiently agreed to be the subject of an interview
Understanding Author Rights
No full textAuthor Rights is the term used to describe a researcher\u27s rights related to their published work. In this session, Brian Young will: 1) provide an overview of author rights, 2) explain language often used in the publication agreement, and 3) demonstrate a tool (Sherpa Romeo) that can be used to quickly understand what default rights you have (and lose) when you publish with a specific journal
Shady trading on the rights market. by Brian Pollard
No full texttag=1 data=Shady trading on the rights market. by Brian Pollard
tag=2 data=Pollard, Brian
tag=3 data=New Doctor,
tag=6 data=Winter 1995
tag=7 data=11-12.
tag=8 data=EUTHANASIA
tag=10 data=Because the spotlight of public attention has been strongly focused on doctors in this debate, the author believes that it is essential that every doctor makes a clear distinction between his or her private views on the practice of euthanasia and its legislation, because the implications in each case are simply not comparable.
tag=11 data=1995/1/5
tag=12 data=95/0224
tag=13 data=CABBecause the spotlight of public attention has been strongly focused on doctors in this debate, the author believes that it is essential that every doctor makes a clear distinction between his or her private views on the practice of euthanasia and its legislation, because the implications in each case are simply not comparable
Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms
No full textLangrock R, Swihart BJ, Caffo BS, Punjabi NM, Crainiceanu CM. Combining hidden Markov models for comparing the dynamics of multiple sleep electroencephalograms. Statistics in Medicine. 2013;32(19):3342-3356
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