Verification, Analytical Validation, and Clinical Validation (V3): The Foundation of Determining Fit-for-Purpose for Biometric Monitoring Technologies (BioMeTs)

Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field

Blockchain technology into the logistics supply chain implementation effectiveness

Technologies currently have a tremendous impact on all spheres of economy, business and a state. They integrally change people’s conception of trade, property, and market entities interaction. Artificial intelligence, additive, informationommunication, green technologies, biotechnologies, and blockchain technologies development and implementation confirm their leadership importance and inevitability in relation to the activities traditional approaches. In the modern world only the companies with flexible vision, equipment and technologies able to instantly reform, adapt to new conditions and challenges, will benefit. The point at issue is Industry 4.0 as a new technological mode emergence

Quantitative storytelling in the making of a composite indicator

The reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures—which ultimately aim to ‘tell a story’, e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction. We thus explore whether a composite indicator can be built to tell ‘more than one story’ and test this in practical contexts. These include measures used in convergence analysis in the field of cohesion policies and a recent case involving the World Bank’s Doing Business Index. Our experiments are built to imagine different constituencies and stakeholders who agree on the use of evidence and of statistical information while differing on the interpretation of what is relevant and vital

Evaluation of the Effectiveness of the Childhood Development Initiative's Mate-Tricks Pro-Social Behaviour After-School Programme

Mate-Tricks is an after-school programme designed to promote pro-social behaviour in Tallaght West (Dublin). Tallaght West has been designated as an area of particular social and economic disadvantage with high levels of unemployment. Mate-Tricks is a bespoke intervention that combines elements of two pro-social behaviour programmes: the Strengthening Families Program (SFP) and Coping Power Program (CPP). The programme is a one-year multi-session after-school programme comprising 59 children-only sessions, 6 parent-only sessions and 3 family sessions, with each session lasting 1½ hours.The intended outcomes of this programme are stated as follows in the Mate-Tricks manual: enhance children's pro-social development; reduce children's anti-social behaviour; develop children's confidence and self-esteem; improve children's problem-solving skills; improve child-peer interactions; develop reasoning and empathy skills; improve parenting skills; improve parent/child interaction. This evaluation reports on the pilot of this programme. Of the 21 outcomes investigated, 19 showed no significant differences between the children who attended Mate-Tricks and the control group. However, there were 2 statistically significant effects of the Mate-Tricks programme and 3 other effects that approached significance. The lack of effects and the few negative effects found in this study replicates findings in several recent studies of after-school behaviour programmes

Making Evaluation Work

Outlines how evaluation has been integrated into grantmaking practices, since the foundation embarked upon a new approach to the field of youth development in 2000

The clinical effectiveness and cost-effectiveness of point-of-care tests (CoaguChek system, INRatio2 PT/INR monitor and ProTime Microcoagulation system) for the self-monitoring of the coagulation status of people receiving long-term vitamin K antagonist therapy, compared with standard UK practice : systematic review and economic evaluation

Funding The National Institute for Health Research Health Technology Assessment programme.Peer reviewedPublisher PD

Are You Tampering With My Data?

We propose a novel approach towards adversarial attacks on neural networks (NN), focusing on tampering the data used for training instead of generating attacks on trained models. Our network-agnostic method creates a backdoor during training which can be exploited at test time to force a neural network to exhibit abnormal behaviour. We demonstrate on two widely used datasets (CIFAR-10 and SVHN) that a universal modification of just one pixel per image for all the images of a class in the training set is enough to corrupt the training procedure of several state-of-the-art deep neural networks causing the networks to misclassify any images to which the modification is applied. Our aim is to bring to the attention of the machine learning community, the possibility that even learning-based methods that are personally trained on public datasets can be subject to attacks by a skillful adversary.Comment: 18 page

Evaluation of the burden of HPV-related hospitalizations as a useful tool to increase awareness: 2007–2017 data from the sicilian hospital discharge records

In light of the implementation of human papillomavirus (HPV) prevention strategies, epidemiological studies in different geographical areas are required in order to assess the impact of HPV-related diseases. The purpose of the present study was to describe the burden of HPV-related hospitalizations in Sicily. A retrospective observational study estimated 43,531 hospitalizations attributable to HPV from 2007 to 2017. During the observed period, there was a decrease for all HPV-related conditions with a higher reduction, among neoplasms, for cervical cancer (annual percent change (APC) = −9.9%, p < 0.001). The median age for cervical cancer was 45 years old, with an increasing value from 43 to 47 years (p < 0.001). The age classes with greater decreases in hospital admissions for invasive cancers were women aged 35 years or more (APC range from −5.5 to −9.86) and 25–34 years old (APC = −11.87, p < 0.001) for women with cervical carcinoma in situ. After ten years for vaccine introduction and sixteen years for cervical cancer screening availability, a relatively large decrease in hospital admissions for cervical cancer and other HPV-related diseases in Sicily was observed. Some clinical characteristics of hospitalization, such as increasing age, are suggestive clues for the impact of preventive strategies, but further research is needed to confirm this relationship