Artificial Intelligence and Machine Learning for Digital Pathology

State-of-the-Art and Future Challenges

Häftad, Engelska, 2020

AvAndreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller,Heimo Muller

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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.

Produktinformation

Utgivningsdatum2020-06-21
Mått155 x 235 x 28 mm
Vikt552 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor341
FörlagSpringer Nature Switzerland AG
ISBN9783030504014

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Informationsteknik: allmänt inom Data och it
Systemvetenskap och AI inom Data och it
Artificiell intelligens inom Data och it
Nätverk och kommunikation inom Data och it
Patologi inom Medicin
Databaser inom Data och it
IT-säkerhet inom Data och it

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 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.