Amalia van Solms and the Formation of the Stadhouder's Art Collection, 1625-1675

This dissertation examines the role of Amalia van Solms (1602-1675), wife of Frederik Hendrik, Prince of Orange and Stadhouder of the United Provinces of the Netherlands (1584-1647), in the formation of the couple's art collection. Amalia and Frederik Hendrik's collection of fine and decorative arts was modeled after foreign, royal courts and they cultivated it to rival those of other great European treasure houses. While some scholars have recognized isolated instances of Amalia's involvement with artistic projects at the Stadhouder's court, this dissertation presents a more comprehensive account of these activities by highlighing specific examples of Amalia's patronage and collecting practices. Through an examination of gifts of art, portraits of Amalia and her porcelain collection, this study considers the ways in which Amalia contributed to the formation of the Stadhouder's art collection. This dissertation seeks to provide a greater knowledge not only of Amalia's activities as a patron and collector, but also a more throrough understanding of the genesis and function of the collection as a whole, which reflected the power and glory of the House of Orange during the Dutch Golden Age

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system's actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings