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This article is the second part in our machine learning series. Part 1 provided a general overview of machine learning in nuclear medicine. Part 2 focuses on neural networks. We start with an example illustrating how neural networks work and a discussion of potential applications. Recognizing that there is a spectrum of applications, we focus on recent publications in the areas of image reconstruction, low-dose PET, disease detection, and models used for diagnosis and outcome prediction. Finally, since the way machine learning algorithms are reported in the literature is extremely variable, we conclude with a call to arms regarding the need for standardized reporting of design and outcome metrics and we propose a basic checklist our community might follow going forward.

The International Solid-State Circuits Conference (ISSCC) is the flagship conference of the IEEE Solid-State Circuits Society. The theme for ISSCC 2020 is "Integrated Circuits Powering the Artificial Intelligence (AI) Era." Advances in solid-state circuits and systems have brought ever more powerful communication and computational capabilities into mobile form factors. Such ubiquitous smart devices lie at the heart of a revolution shaping how we connect, collaborate, build relationships, and share information. These social technologies enable people to maintain connections and support networks not otherwise possible; they provide the ability to access information instantaneously and from any location, thereby helping to shape world events and culture, empower citizens of all nations, and create social networks that help worldwide communities develop and form bonds based on common interests.

This article, the first in a 2-part series, provides an introduction to machine learning (ML) in a nuclear medicine context. This part addresses the history of ML and describes common algorithms, with illustrations of when they can be helpful in nuclear medicine. Part 2 focuses on current contributions of ML to our field, addresses future expectations and limitations, and provides a critical appraisal of what ML can and cannot do.

The International Solid-State Circuits Conference (ISSCC) is the flagship conference of the IEEE Solid-State Circuits Society. This year, for the 65th ISSCC, the theme is "Silicon Engineering a Social World." Continued advances in solid-state circuits and systems have brought ever-more powerful communication and computational capabilities into mobile form factors. Such ubiquitous smart devices lie at the heart of a revolution shaping how we connect, collaborate, build relationships, and share information. These social technologies allow people to maintain connections and support networks not otherwise possible; they provide the ability to access information instantaneously and from any location, thereby helping to shape world events and culture, empowering citizens of all nations, and creating social networks that allow worldwide communities to develop and form bonds based on common interests.

The International Solid-State Circuits Conference (ISSCC) is the flagship conference of the IEEE Solid-State Circuits Society. This year, the theme for ISSCC 2017 is "Intelligent Chips for a Smart World." Advances in solid-state circuits and systems continue to propel the ongoing fusion between the physical and virtual worlds. With the resulting growth in sensor deployment, data traffic, and data-center workloads, future systems must employ "intelligent" chips at all levels of the system stack to improve the efficiency at which we acquire, network, store, and process information. Modern applications centered around the Internet of Everything (IoE) and real-time data analytics are driving circuit and system designers toward new ways of leveraging the immense device density and processing power of modern technology. ISSCC covers a spectrum of design approaches in various technical areas and advances, broadly categorized as analog systems, analog-to-digital data-conversion systems, communication systems, digital systems, and innovative topics such as micromachines and microelectromechanical systems (MEMS), imagers, sensors, and biomedical devices, as well as forward-looking solutions that may be several years away from becoming commercial. The ten ISSCC technical subcommittees annually update their analyses of industry trends for the benefit of the community at large. This article summarizes some of these views in selected technical areas.

In addition to opening the book, this chapter serves as a brief overview of the historical advances in stochastic computing. We highlight four distinct eras, including early work from the 1950s, fundamental work in the 1960s, an era of slower progress in the 1970s, 1980s, and 1990s, and a return to prominence in the 2000s.

Between 2007 and 2014, 337 free-living red squirrels (

A two-part article, ?Through the Looking Glass II? was published last year (in the Winter 2013 and Spring 2013 issues of IEEE Solid-State Circuits Magazine) to discuss the trends in solid-state circuits and systems based on papers selected by the program subcommittees of IEEE International Solid-State Circuits Conference (ISSCC) 2013. This article highlights additions to those trends based on technical papers that are selected to be presented at ISSCC 2014.