Artificial intelligence and machine learning for digital pathology : state-of-the-art and future challenges /: state-of-the-art and future challenges. ([2020])

• Record Type: Book
• Further Information: Note: Andreas Holzinger, Randy Goebel, Michael Mengel, Heimo Müller (eds.).
• Other Names: Holzinger, Andreas; Goebel, Randy; Mengel, Michael; Müller, Heimo
• Contents: Intro -- Preface -- Organization -- Contents -- About the Editors -- Expectations of Artificial Intelligence for Pathology -- 1 Introduction and Motivation -- 1.1 What Is the Difference Between Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL)? -- 1.2 Is Pathology an Uncomplicated Medical Speciality? -- 2 Glossary -- 3 State-of-the-Art -- 3.1 The Position of AI in Pathology Today? -- 3.2 Where Could Pathologists Need Support by AI? -- 4 Open Problems -- 5 Future Outlook -- References Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images -- 1 Introduction and Motivation -- 2 Glossary -- 3 State of the Art -- 3.1 Prediction of er Status Using nn -- 3.2 Post-hoc Model Explanation -- 4 Methods -- 4.1 Data and Preprocessing -- 4.2 Training and Evaluation -- 4.3 Visual Explanation of er Status Predictions -- 5 Experiments -- 5.1 Hyperparameter Tuning and Performance Evaluation -- 5.2 Comparison to a State-of-the-Art Method -- 5.3 Variance over the Splits -- 5.4 Rejection Option -- 5.5 Visual Explanation -- 6 Discussion -- 7 Conclusion 8 Open Challenges and Future Work -- References -- Supporting the Donation of Health Records to Biobanks for Medical Research -- 1 Introduction -- 2 A Motivating Scenario -- 3 ELGA -- A Prototypical Mediator of Health Records -- 4 Stakeholders -- 4.1 Donors -- 4.2 Researchers -- 4.3 General Public -- 4.4 Health Care Providers -- 4.5 Mediators -- 5 Laws and Regulations -- 5.1 European General Data Protection Regulation -- 5.2 Laws Governing Health Data Mediators -- 6 Interoperability Requirements -- 6.1 ELGA Infrastructure -- 6.2 ELGA Documents -- 7 Incentivizing Data Donation by Building Trust 7.1 Security and Privacy -- 7.2 Access Control and Monitoring -- 7.3 Information -- 7.4 Ethical Principles -- 7.5 Informed Consents -- 8 Electronic Informed Consent with Disclosure Filters -- 8.1 Example -- 8.2 Electronic Informed Consent (eIC) -- 8.3 Disclosure Filter Specification -- 9 Discussion and Conclusions -- References -- Survey of XAI in Digital Pathology -- 1 Introduction and Motivation -- 1.1 Background -- 1.2 AI in Pathology -- 1.3 Needs of XAI in Digital Pathology -- 2 Glossary -- 3 State-of-the-Art -- 3.1 Explanation Target -- 3.2 Result Representation -- 3.3 Technical Approach 3.4 XAI Methods in Medical Imaging -- 4 Open Problems -- 5 Future Outlook -- A Reviewed Methods -- References -- Sample Quality as Basic Prerequisite for Data Quality: A Quality Management System for Biobanks -- 1 Introduction and Motivation -- 2 Glossary -- 3 State-of-the-Art -- 3.1 The Quality Management Concept of GBN -- 3.2 QM Manual -- 3.3 Software Solution -- 3.4 Friendly Audits -- 3.5 Ring Trials -- 3.6 Satisfaction Survey for Biobank Users -- 4 Challenges and Opportunities -- 5 Outlook -- References
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2020
• Extent: 1 online resource, illustrations
• Subjects: 616.07; Pathology -- Data processing; Artificial intelligence -- Medical applications; Machine learning; Electronic books; Pathology -- methods5; Electronic books
• Languages: English
• ISBNs: 9783030504021; 3030504026
• Related ISBNs: 3030504018; 9783030504014
• Notes: Note: Includes bibliographical references and index.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.