Crosscope

Curated on Posted on by Stefaan Verhulst

“Crosscope is revolutionizing the way practitioners and researchers are leveraging digital pathology to share and solve medical cases.

Since the 1900s cancer diagnosis has been limited to the subjective interpretation of what the pathologist could see under a microscope. To transform the way we perform pathology and cancer research, we are developing new tools to leverage powerful AI & perspectives of medical experts at the same time.

At Crosscope, we are building a place for the convergence of collective intelligence of our massive online medical community and AI. We are commited to developing cutting edge AI tools for better decision support in cancer care. We aim to be the largest database for tagged histopathology images which will contain a lot more information than genomics alone and will be crucial in early diagnosis of cancer….(More)”.

AI Ethics — Too Principled to Fail?

Curated on Posted on by Stefaan Verhulst

Paper by Brent Mittelstadt: “AI Ethics is now a global topic of discussion in academic and policy circles. At least 63 public-private initiatives have produced statements describing high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. According to recent meta-analyses, AI Ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics.

Despite the initial credibility granted to a principled approach to AI Ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach in the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement….(More)”.

Sharing data can help prevent public health emergencies in Africa

Curated on Posted on by Stefaan Verhulst

Moses John Bockarie at The Conversation: “Global collaboration and sharing data on public health emergencies is important to fight the spread of infectious diseases. If scientists and health workers can openly share their data across regions and organisations, countries can be better prepared and respond faster to disease outbreaks.

This was the case in with the 2014 Ebola outbreak in West Africa. Close to 100 scientists, clinicians, health workers and data analysts from around the world worked together to help contain the spread of the disease.

But there’s a lack of trust when it comes to sharing data in north-south collaborations. African researchers are suspicious that their northern partners could publish data without acknowledging the input from the less resourced southern institutions where the data was first generated. Until recently, the authorship of key scientific publications, based on collaborative work in Africa, was dominated by scientists from outside Africa.

The Global Research Collaboration for Infectious Disease Preparedness, an international network of major research funding organisations, recently published a roadmap to data sharing. This may go some way to address the data sharing challenges. Members of the network are expected to encourage their grantees to be inclusive and publish their results in open access journals. The network includes major funders of research in Africa like the European Commission, Bill & Melinda Gates Foundation and Wellcome Trust.

The roadmap provides a guide on how funders can accelerate research data sharing by the scientists they fund. It recommends that research funding institutions make real-time, external data sharing a requirement. And that research needs to be part of a multi-disciplinary disease network to advance public health emergencies responses.

In addition, funding should focus on strengthening institutions’ capacity on a number of fronts. This includes data management, improving data policies, building trust and aligning tools for data sharing.

Allowing researchers to freely access data generated by global academic counterparts is critical for rapidly informing disease control strategies in public health emergencies….(More)”.

Ebola outbreak demonstrates science’s need to ‘nudge’

Curated on Posted on by Stefaan Verhulst

Anjana Ahuja at the Financial Times: “It should be a moment of cautious optimism: a second promising vaccine has become available to tackle the Ebola outbreak in the Democratic Republic of Congo. Instead, there is uncertainty and angst. Clinicians desperately want to see the new vaccine deployed. But officials in the DRC, unnerved by public reaction to an earlier experimental vaccine, worry that introducing a second one might stoke public suspicions and destabilise containment efforts.

Experts met in the capital Kinshasa last week to work out which way to jump. The dilemma illustrates that human behaviour can be as destructive to global health as any deadly pathogen. Addressing diseases — even the organ-destroying horror that is Ebola — is no longer a matter of merely concocting a vaccine but also persuading people to roll up their sleeves for it. Some academics are even calling for the World Health Organization to establish its own “nudge unit” to apply lessons from behavioural science. While dealing with disease outbreaks “require[s] modifying or working with human behaviour”, they wrote recently in Scientific American, “the global response to these threats lacks a coherent focus on behavioural insights.”…(More)”

Clinical Trial Data Transparency and GDPR Compliance: Implications for Data Sharing and Open Innovation

Curated on Posted on by Stefaan Verhulst

Paper by Timo Minssen, Rajam N. and Marcel Bogers: “Recent EU initiatives and legislations have considerably increased public access to clinical trials data (CTD). These developments are generally much welcomed for the enhancement of science, trust, and open innovation. However, they also raise many questions and concerns, not least at the interface between CTD transparency and other areas of evolving EU law on the protection of trade secrets, intellectual property rights and privacy.

This paper focuses on privacy issues and on the interrelation between developments in transparency and the EU’s new General Data Protection Regulation 2016/679 (GDPR). More specifically, this paper examines: (1) the genesis of EU transparency regulations, including the incidents, developments and policy concerns that have shaped them; (2) the features and implications of the GDPR which are relevant in the context of clinical trials; and (3) the risk for tensions between the GDPR and the policy goals of CTD transparency, including their implications for data sharing and open innovation. Ultimately, we stress that these and other related factors must be carefully considered and addressed to reap the full benefits of CTD transparency….(More)”.

Google and the University of Chicago Are Sued Over Data Sharing

Curated on Posted on by Stefaan Verhulst

Daisuke Wakabayashi in The New York Times: “When the University of Chicago Medical Center announced a partnership to share patient data with Google in 2017, the alliance was promoted as a way to unlock information trapped in electronic health records and improve predictive analysis in medicine.

On Wednesday, the University of Chicago, the medical center and Google were sued in a potential class-action lawsuit accusing the hospital of sharing hundreds of thousands of patients’ records with the technology giant without stripping identifiable date stamps or doctor’s notes.

The suit, filed in United States District Court for the Northern District of Illinois, demonstrates the difficulties technology companies face in handling health data as they forge ahead into one of the most promising — and potentially lucrative — areas of artificial intelligence: diagnosing medical problems.

Google is at the forefront of an effort to build technology that can read electronic health records and help physicians identify medical conditions. But the effort requires machines to learn this skill by analyzing a vast array of old health records collected by hospitals and other medical institutions.

That raises privacy concerns, especially when is used by a company like Google, which already knows what you search for, where you are and what interests you hold.

In 2016, DeepMind, a London-based A.I. lab owned by Google’s parent company, Alphabet, was accused of violating patient privacy after it struck a deal with Britain’s National Health Service to process medical data for research….(More)”.

The clinician crowdsourcing challenge: using participatory design to seed implementation strategies

Curated on Posted on by Stefaan Verhulst

Paper by Rebecca E. Stewart et al: “In healthcare settings, system and organization leaders often control the selection and design of implementation strategies even though frontline workers may have the most intimate understanding of the care delivery process, and factors that optimize and constrain evidence-based practice implementation within the local system. Innovation tournaments, a structured participatory design strategy to crowdsource ideas, are a promising approach to participatory design that may increase the effectiveness of implementation strategies by involving end users (i.e., clinicians). We utilized a system-wide innovation tournament to garner ideas from clinicians about how to enhance the use of evidence-based practices (EBPs) within a large public behavioral health system…(More)”

From Theory to Practice : Open Government Data, Accountability, and Service Delivery

Curated on Posted on by Stefaan Verhulst

Report by Michael Christopher Jelenic: “Open data and open government data have recently attracted much attention as a means to innovate, add value, and improve outcomes in a variety of sectors, public and private. Although some of the benefits of open data initiatives have been assessed in the past, particularly their economic and financial returns, it is often more difficult to evaluate their social and political impacts. In the public sector, a murky theory of change has emerged that links the use of open government data with greater government accountability as well as improved service delivery in key sectors, including health and education, among others. In the absence of cross-country empirical research on this topic, this paper asks the following: Based on the evidence available, to what extent and for what reasons is the use of open government data associated with higher levels of accountability and improved service delivery in developing countries?

To answer this question, the paper constructs a unique data set that operationalizes open government data, government accountability, service delivery, as well as other intervening and control variables. Relying on data from 25 countries in Sub-Saharan Africa, the paper finds a number of significant associations between open government data, accountability, and service delivery. However, the findings suggest differentiated effects of open government data across the health and education sectors, as well as with respect to service provision and service delivery outcomes. Although this early research has limitations and does not attempt to establish a purely causal relationship between the variables, it provides initial empirical support for claims about the efficacy of open government data for improving accountability and service delivery….(More)”

The European Lead Factory: Collective intelligence and cooperation to improve patients’ lives

Curated on Posted on by Stefaan Verhulst

Press Release: “While researchers from small and medium-sized companies and academic institutions often have enormous numbers of ideas, they don’t always have enough time or resources to develop them all. As a result, many ideas get left behind because companies and academics typically have to focus on narrow areas of research. This is known as the “Innovation Gap”. ESCulab (European Screening Centre: unique library for attractive biology) aims to turn this problem into an opportunity by creating a comprehensive library of high-quality compounds. This will serve as a basis for testing potential research targets against a wide variety of compounds.

Any researcher from a European academic institution or a small to medium-sized enterprise within the consortium can apply for a screening of their potential drug target. If a submitted target idea is positively assessed by a committee of experts it will be run through a screening process and the submitting party will receive a dossier of up to 50 potentially relevant substances that can serve as starting points for further drug discovery activities.

ESCulab will build Europe’s largest collaborative drug discovery platform and is equipped with a total budget of € 36.5 million: Half is provided by the European Union’s Innovative Medicines Initiative (IMI) and half comes from in-kind contributions from companies of the European Federation of Pharmaceutical Industries an Associations (EFPIA) and the Medicines for Malaria Venture. It builds on the existing library of the European Lead Factory , which consists of around 200,000 compounds, as well as around 350,000 compounds from EFPIA companies. The European Lead Factory aims to initiate 185 new drug discovery projects through the ESCulab project by screening drug targets against its library.

… The platform has already provided a major boost for drug discovery in Europe and is a strong example of how crowdsourcing, collective intelligence and the cooperation within the IMI framework can create real value for academia, industry, society and patients….(More)”

Opening Data for Global Health

Curated on Posted on by Stefaan Verhulst

Chapter by Matt Laessig, Bryon Jacob and Carla AbouZahr in The Palgrave Handbook of Global Health Data Methods for Policy and Practice: “…provide best practices for organizations to adopt to disseminate data openly for others to use. They describe development of the open data movement and its rapid adoption by governments, non-governmental organizations, and research groups. The authors provide examples from the health sector—an early adopter—but acknowledge concerns specific to health relating to informed consent, intellectual property, and ownership of personal data. Drawing on their considerable contributions to the open data movement, Laessig and Jacob share their Open Data Progression Model. They describe six stages to make data open: from data collection, documentation of the data, opening the data, engaging the community of users, making the data interoperable, to finally linking the data….(More)”