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A Human-Centered Evaluation of a Deep Learning System Deployed in Clinics for the Detection of Diabetic Retinopathy

This paper contributes the first human-centered observational study of a deep learning system deployed directly in clinical care with patients. Through field observations and interviews at eleven clinics across Thailand, we explored the expectations and realities that nurses encounter in bringing a deep learning model into their clinical practices. First, we outline typical eye-screening workflows and challenges that nurses experience when screening hundreds of patients. Then, we explore the expectations nurses have for an AI-assisted eye screening process. Next, we present a human-centered, observational study of the deep learning system used in clinical care, examining nurses’ experiences with the system, and the socio-environmental factors that impacted system performance. Finally, we conclude with a discussion around applications of HCI methods to the evaluation of deep learning algorithms in clinical environments.

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A socio-technical framework for digital contact tracing

In their efforts to tackle the COVID-19 crisis, decision makers are considering the development and use of smartphone applications for contact tracing. Even though these applications differ in technology and methods, there is an increasing concern about their implications for privacy and human rights. Here we propose a framework to evaluate their suitability in terms of impact on the users, employed technology and governance methods.

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#Standards4Quantum: Making Quantum Technology Ready for Industry

The Joint Research Center (JRC) in cooperation with the European Committee for Standardization (CEN) and the European Committee for Electrotechnical Standardization (CENELEC), European Commission’s Directorate General Communications Networks, Content and Technology (DG CNECT), and the German Institute of Standardisation (DIN), organised in Brussels on 28-29 March 2019 the Putting-Science-Into-Standards (PSIS) workshop on Quantum Technologies.

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The European Data Protection Supervisor, 2019 Annual Report a year of transition

With new legislation on data protection in the EU now in place, our greatest challenge moving into 2020 is to ensure that this legislation produces the promised results. This includes ensuring that new rules on ePrivacy remain firmly on the EU agenda. Awareness of the issues surrounding data protection and privacy and the importance of rotecting these fundamental rights is at an all time high and we cannot allow this momentum to decline.

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Google Engineering Practices Documentation

Google has many generalized engineering practices that cover all languages and all projects. These documents represent their collective experience of various best practices that they have developed over time. It is possible that open source projects or other organizations would benefit from this knowledge.

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SciPy Programming Succinctly

The SciPy library, accompanied by its interdependent NumPy, offers Python programmers advanced functions that work with arrays and matrices. Each section presents a complete demo program for programmers to experiment with, carefully chosen examples to best illustrate each function, and resources for further learning. Use this e-book to install and edit SciPy, and use arrays, matrices, and combinatorics in Python programming.

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Data Structures Succinctly Part 2

Data Structures Succinctly Part 2 is your concise guide to skip lists, hash tables, heaps, priority queues, AVL trees, and B-trees. As with the first book, you’ll learn how the structures behave, how to interact with them, and their performance limitations. Starting with skip lists and hash tables, and then moving to complex AVL trees and B-trees, author Robert Horvick explains what each structure’s methods and classes are, the algorithms behind them, and what is necessary to keep them valid.

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The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective—from a product view to a system view—is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies like the FDA who are used to regulating products, not systems. We offer several suggestions for regulators to make this challenging but important transition

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Data Structures Succinctly Part 1

Data Structures Succinctly Part 1 is your first step to a better understanding of the different types of data structures, how they behave, and how to interact with them. Starting with simple linked lists and arrays, and then moving to more complex structures like binary search trees and sets, author Robert Horvick explains what each structure’s methods and classes are and the algorithms behind them. Horvick goes a step further to detail their operational and resource complexity, ensuring that you have a clear understanding of what using a specific data structure entails.

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When Autonomous Vehicles Are Hacked, Who Is Liable?

Who might face civil liability if autonomous vehicles (AVs) are hacked to steal data or inflict mayhem, injuries, and damage? How will the civil justice and insurance systems adjust to handle such claims? RAND researchers addressed these questions to help those in the automotive, technology, legal, and insurance industries prepare for the shifting roles and responsibilities that the era of AVs may bring.