PlatformTM, a standards-based data custodianship platform for translational medicine research

resistancebank.org, an open-access repository for surveys of antimicrobial resistance in animals

Antimicrobial resistance (AMR) is a growing threat to the health of humans and animals that requires global actions. In high-income countries, surveillance systems helped inform policies to curb AMR in animals. In low- and middle-income countries (LMICs), demand for meat is rising, and developing policies against AMR is urgent. However, surveillance of AMR is at best nascent, and the current evidence base to inform policymakers is geographically heterogeneous. We present resistancebank.org, an online platform that centralizes information on AMR in animals from 1,285 surveys from LMICs. Surveys were conducted between 2000 and 2019 and include 22,403 resistance rates for pathogens isolated from chickens, cattle, sheep, and pigs. The platform is built as a shiny application that provides access to individual surveys, country-level reports, and maps of AMR at 10 × 10 kilometers resolution. The platform is accessed via any internet browser and enables users to upload surveys to strengthen a global database. resistancebank.org aims to be a focal point for sharing AMR data in LMICs and to help international funders prioritize their actions.

Social innovation for life expectancy extension utilizing a platform-centered system used in the Iwaki health promotion project: A protocol paper

Introduction:

We are trying to create a platform for social innovation to extend life span.

Methods:

Since 2005, health data (approximately 3000 items per person as of 2020) of approximately 1000 adults have been collected each year during the Iwaki Health Promotion Project. The industry, government, academia, and citizens have involvements in data collection, aiming to build a platform that encourages societal innovation and subsequently extends life expectancy in Aomori. The Iwaki Health Promotion Project has been supported financially by the Japanese government since it was selected as the Center of Innovation program in 2013.

Results:

Since the numbers of academia, industries, governments, and citizens involved in the Iwaki Health Promotion Project increased over the years, the big data produced during the project has become increasingly pluripotent and adaptable. It has been used to promote public health, which has also created a stronger partnership among companies and research organizations. Consequently, the amount of data collected from the project has gained attention and became more open to companies and researchers participating in the Iwaki Health Promotion Project, resulted in establishing a larger platform. It also led to the acquisition of external funding, publications of numerous research papers, creation of new health examinations, and the establishment of the Health Promotion Center (an institution for cultivating health volunteers).

Conclusion:

The Iwaki Health Promotion Project aims not only to produce a pluripotent big data but also to improve the average life expectancy of Aomori by creating a large platform in the society. Its positive impact in the future is infinite and will keep growing as long as it is maintained by the society.

Accelerating ophthalmic artificial intelligence research: the role of an open access data repository

PURPOSE OF REVIEW

Artificial intelligence has already provided multiple clinically relevant applications in ophthalmology. Yet, the explosion of nonstandardized reporting of high-performing algorithms are rendered useless without robust and streamlined implementation guidelines. The development of protocols and checklists will accelerate the translation of research publications to impact on patient care.

RECENT FINDINGS

Beyond technological scepticism, we lack uniformity in analysing algorithmic performance generalizability, and benchmarking impacts across clinical settings. No regulatory guardrails have been set to minimize bias or optimize interpretability; no consensus clinical acceptability thresholds or systematized postdeployment monitoring has been set. Moreover, stakeholders with misaligned incentives deepen the landscape complexity especially when it comes to the requisite data integration and harmonization to advance the field. Therefore, despite increasing algorithmic accuracy and commoditization, the infamous 'implementation gap' persists. Open clinical data repositories have been shown to rapidly accelerate research, minimize redundancies and disseminate the expertise and knowledge required to overcome existing barriers. Drawing upon the longstanding success of existing governance frameworks and robust data use and sharing agreements, the ophthalmic community has tremendous opportunity in ushering artificial intelligence into medicine. By collaboratively building a powerful resource of open, anonymized multimodal ophthalmic data, the next generation of clinicians can advance data-driven eye care in unprecedented ways.

SUMMARY

This piece demonstrates that with readily accessible data, immense progress can be achieved clinically and methodologically to realize artificial intelligence's impact on clinical care. Exponentially progressive network effects can be seen by consolidating, curating and distributing data amongst both clinicians and data scientists.