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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.
Antioxidant Polymers is an exhaustive overview of the recent developments in the field of polymeric materials showing antioxidant properties. This research area has grown rapidly in the last decade because antioxidant polymers have wide industry applications ranging from materials science to biomedical, pharmaceuticals and cosmetics.
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Since their discovery in 1869, the dictyostelids have attracted the attention of scientists in a wide variety of fields. This interest has stemmed from their peculiar lifestyle and developmental properties, which were shaped by the evolutionary forces that generated multicellularity during eukaryotic evolution. More recently, the dictyostelids have gained attention due to the striking similarities found at the genomic, cellular and biochemical levels with human cells, which has propelled the species Dictyostelium discoideum to become a model system for biology and medicine in many laboratories. This book covers the latest advances in our knowledge of these extraordinary organisms with topics spanning from their evolutionary history, ecology and diversity to the recent discoveries regarding their cellular and molecular biology.