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1. |
Record Nr. |
UNINA9910451308903321 |
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Titolo |
Transparency and other hot topics revisited [[electronic resource] /] / guest editors, Tom McManus ... [et al.] |
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Pubbl/distr/stampa |
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[Bradford], : Emerald, [2007] |
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ISBN |
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1-280-92905-7 |
9786610929054 |
1-84663-457-1 |
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Descrizione fisica |
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1 online resource (128 p.) |
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Collana |
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Journal of management development, , 0262-1711 ; ; v. 26, no. 5 (2007) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Executives - Training of |
Middle managers - Training of |
Business ethics |
Disclosure of information |
Communication in organizations |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Cover; CONTENTS; EDITORIAL ADVISORY BOARD; Guest editorial; Breaking-out-of-the-box in organizations; Organizational transparency drives company performance; Challenges in achieving transparency, simplicity and administering of the United States tax code; Entrepreneurship in Egypt and the US compared: directions for further research suggested; An equation of health; Transition and transparency in the employment contract; Dave Delaney's useful advice for your development as a manager; Working from the inside out; Retirement - an unaffordable luxury |
Through the looking glass: illusions of transparency and the cult of informationThe best of the best: lessons from the top performing American corporations, 1954-2005 |
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Sommario/riassunto |
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This e-book follows up the 2006 e-book with a further exploration of transparency. The editors explore how transparency is interpreted and |
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applied across a range of areas, including human resources, tax systems, healthcare provision; retirement and organizational communication. The e-book features contributions from an international team of authors. |
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2. |
Record Nr. |
UNINA9910166460303321 |
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Autore |
Corletto, Federico |
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Titolo |
Anestesia del cane e del gatto / Federico Corletto |
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Pubbl/distr/stampa |
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Vermezzo, : Poletto, 2010 |
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ISBN |
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Edizione |
[2. ed.] |
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Descrizione fisica |
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Disciplina |
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Locazione |
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Collocazione |
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636.089796 COR1 |
636.089796 COR1bis |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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3. |
Record Nr. |
UNINA9910410055503321 |
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Titolo |
Artificial Intelligence and Machine Learning for Digital Pathology : State-of-the-Art and Future Challenges / / edited by Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (xii, 339 pages) |
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Collana |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 12090 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computers |
Database management |
Social sciences - Data processing |
Data protection |
Computer vision |
Artificial Intelligence |
Computing Milieux |
Database Management |
Computer Application in Social and Behavioral Sciences |
Data and Information Security |
Computer Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Expectations of Artificial Intelligence for Pathology -- Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images -- Supporting the Donation of Health Records to Biobanks for Medical Research -- Survey of XAI in Digital Pathology -- Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks -- Black Box Nature of Deep Learning for Digital Pathology: Beyond Quantitative to Qualitative Algorithmic Performances -- Towards a Better Understanding of the |
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Workflows: Modeling Pathology Processes in View of Future AI Integration -- OBDEX – Open Block Data Exchange System -- Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A Review -- Higher Education Teaching Material on Machine Learning in the Domain of Digital Pathology -- Classification vs Deep Learning in Cancer Degree on Limited Histopathology Datasets -- Biobanks and Biobank-Based Artificial Intelligence (AI) Implementation Throughan International Lens -- HistoMapr: An Explainable AI (xAI) Platform for Computational Pathology Solutions -- Extension of the Identity Management System Mainzelliste to Reduce Runtimes for Patient Registration in Large Datasets -- Digital Image Analysis in Pathology Using DNA Stain: Contributions in Cancer Diagnostics and Development of Prognostic and Theranostic Biomarkers -- Assessment and Comparison of Colour Fidelity of Whole slide imaging scanners -- Deep Learning Methods for Mitosis Detection in Breast Cancer Histopathological Images: a Comprehensive Review -- Developments in AI and Machine Learning for Neuroimaging. |
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Sommario/riassunto |
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Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions. |
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