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Breaking News Coronavirus Update: Vaccine Ready for Human Trials A vaccine for the novel coronavirus has been developed and is ready for human trials, according to the World Health Organization. The vaccine is a combination of two existing vaccines that have been modified to target the virus that causes COVID-19. Clinical trials will begin in the coming weeks and the vaccine could be ready for use by the end of the year. Read more here Article: How to Stay Positive During Coronavirus Outbreak The coronavirus pandemic has upended our lives and left us feeling anxious, uncertain, and overwhelmed. But despite the difficult times, it is important to stay positive. Here are some tips for doing just that: Focus on what you
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Decoding the Language of Data: How Natural Language Processing is Transforming Financial Forecasting - DataScienceVerse
“`html Have you ever found yourself staring at a sea of financial data, feeling as if you were trying to decode ancient hieroglyphics? Well, you’re not alone! The world of finance is a dizzying landscape filled with numbers, trends, and forecasts that can bewilder even the most seasoned professionals. But fear not! Natural Language Processing […]
Navigating the Dark Side of AI: Real Stories from Data Scientists on Bias and Fairness - DataScienceVerse
“`html When the buzz around artificial intelligence (AI) started to permeate every aspect of our lives, I was both excited and a bit apprehensive. Sure, the promise of smart devices, automated systems, and enhanced data processing sounded fantastic, but lurking beneath this shiny surface was a gritty reality: bias and fairness are not just buzzwords; […]
Data Science Under the Hood: Real-World Challenges and Triumphs in Algorithm Debugging - DataScienceVerse
“`html Welcome to the chaotic yet fascinating realm of data science! It’s a world where algorithms reign supreme, all while we wear our battle scars from the trenches of debugging. Today, we dive deep into the gears and levers of Data Science, exploring the real-world challenges and unexpected triumphs that come with it. Buckle up, […]
Agents, APIs, and the Next Layer of the Internet | Towards Data Science
Part I: Shipping Containers for Thought Every so often a simple idea rewires everything. The shipping container didn’t just optimise logistics; it flattened the globe, collapsed time zones, and rewrote the economics of trade. In its geometric austerity was a quiet revolution: standardisation. Similarly, HTML and HTTP didn’t invent information exchange — any more than […]
Shiny in Production 2025: Full Length Talks | R-bloggers
We are pleased to announce the full line-up for this year’s Shiny in Production conference! The conference includes nine full-length talks (25 minutes each) and a lightning talk session (5 minutes per talk), we’ll cover those in a separate blog. Register now Talks Cameron Race - Head of Children and Schools Statistics and Product Manager shinyGovstyle: A ‘Shiny’ Secret Weapon for Production-Ready Government Public Services In the UK, we are required to make public sector websites accessible to all users. While there is a wealth of UK government data publicly available through a number of existing digital services, it can be tough to engage with. Government analysts are increasingly turning to R Shiny to enhance their data dissemination, making it more engaging for users, but with hundreds of analysts working in silos across government, how can analysts build full digital services in a way that carries the same consistency, trustworthiness and authority as a domain such as GOV.UK? Charlie Gao - Posit Software, PBC Advances in the Shiny Ecosystem Charlie Gao, Senior Software Engineer on Posit’s open source team will review some of the latest high-performance async tooling developed by Posit to support R Shiny in terms of performance, scalability and user experience. Colin Fay - ThinkR After {shiny} — Bringing R to Mobile with webR As the use of mobile devices becomes increasingly central to how users interact with data products, the R community has long sought ways to bring R-powered applications into the mobile space. Historically, this has meant adapting {shiny} apps for smaller screens—either through responsive design or packages like {shinyMobile}. While effective for certain use cases, these approaches are fundamentally web-based, requiring a server and a stable internet connection, and lacking access to native device features. This talk presents a new path forward: Rlinguo, a fully native mobile application built with webR, a version of R compiled to WebAssembly. Unlike traditional {shiny}-based solutions, Rlinguo runs R directly on the device, without a server. It works offline, stores data locally, and can leverage native mobile APIs—pushing the boundaries of what’s possible with R in a mobile context. Through this case study, we’ll explore the architecture behind Rlinguo, contrast it with the {shiny} model, and discuss what it means for the future of R development. Topics will include: What it takes to embed R in a mobile app using webR Technical and design trade-offs between web-based and native solutions Practical applications for offline, device-integrated R tools Whether you’re building with {shiny} today or simply curious about the next evolution of R in production, this session offers a look at where R can go when it steps beyond the browser. Gabriela De Lima Marin - Brazilian Network Information Centre Bringing Connectivity Data Together: An R Shiny Platform for Public Schools This project presents a collaborative initiative aimed at improving the geolocation accuracy of Brazilian public schools through an interactive Shiny web application. By integrating existing location data from the Brazilian School Census with APIs from Google, Microsoft, and OpenStreetMap, we established an innovative workflow to assign accurate geographic coordinates to schools previously lacking precise location data. The Shiny application provides a user-friendly interface allowing school administrators and education managers to visually verify and manually adjust school locations via interactive maps. Over the past two years, this approach enabled the precise geolocation of previously unlocated schools and significantly enhanced the accuracy of geolocation data of schools. The geolocation data collected and validated through this project will be openly shared with relevant governmental stakeholders, promoting transparency and supporting evidence-based decision-making. Moreover, the project exemplifies how collaborative data science and innovative web technology—particularly R Shiny—can be effectively leveraged in public administration, enabling managers, stakeholders, and the community to directly contribute to data accuracy and positively influence educational outcomes in Brazil. Jack Anderson - National Disease Registration Service, NHS England Transforming the reporting of national patient outcomes with Shiny: 30-day mortality post-Systemic Anti-Cancer Therapy In June 2020, the National Disease Registration Service began reporting 30-day mortality post-Systemic Anti-Cancer Therapy (SACT) Case-Mix Adjusted Rates (CMAR) to NHS trusts in England. This work applies logistic regression to report trust-level case-mix adjusted 30-day mortality rates, which enable comparisons between trusts and with the national average. Historically, results were shared as an Excel workbook with an accompanying companion brief and FAQ document, and each report was shared in isolation from previous releases. Since April 2023, implementation of R Shiny has enabled 30-day mortality rates to be reported seamlessly on an interactive, publicly accessible dashboard. Utilising the Plotly and DT packages, dynamic funnel plots and data tables are tailored to user needs through Shiny input pickers, which reactively subset and summarise data visualisations based on user selections. This enables NHS trust users to flexibly review their 30-day mortality outcomes against those of other trusts, their wider Cancer Alliance, and national averages, both overall and stratified by key patient demographics. The Shiny dashboard also enables users to view current and previous CMAR reports together in one place and includes download button functionality for documentation and underlying data. With dedicated tabs for summary data, trust exclusions, and trust response statements, Shiny allows for end-to-end exploration of CMAR outcomes, making it easier for users to gain insight into clinical practice. The resulting Shiny dashboard supports clinical governance within trusts and enables clinical colleagues to better understand their patient outcomes within their wider context. Laura Mawer & Marcus Palmer - Datacove, Harrison-Palmer Limited Using Shiny for Python to Power AI-Driven University Application Forecasting Universities face growing uncertainty in student recruitment, making accurate forecasting critical for strategic and financial planning. Athena is an AI-powered prediction tool that leverages Shiny for Python to provide real-time insights into application trends. By combining machine learning (Random Forest models), trend analysis, and interactive scenario planning, Athena enables universities to test recruitment strategies, adjust campaign spending, and instantly see the projected impact on future application numbers. This talk will explore how Shiny for Python was used to develop a fully interactive forecasting tool without requiring extensive front-end development. We will discuss why Shiny for Python was chosen, how it integrates with a machine learning pipeline, and how it powers real-time scenario analysis with dynamic dashboards. Additionally, we’ll demonstrate how AI-generated recommendations via an API enhance decision-making, providing actionable insights tailored to user-selected scenarios. Attendees will gain practical knowledge on building AI-driven, interactive applications using Shiny for Python, implementing predictive models, and designing intuitive decision-support tools for non-technical users. The session will conclude with a live demo, showing Athena in action and sharing best practices for deploying Shiny for Python in production. This talk is designed for developers, data scientists, engineers, and senior decision-makers looking to leverage AI-powered forecasting, business intelligence, and strategic planning in a real-world application. Nic Crane - NC Data Labs htmlwidgets Are a Secret Sauce in R – Can LLMs Make Them the Perfect Condiment? htmlwidgets quietly power some of the most compelling Shiny apps out there, but writing them from scratch can be fiddly and time-consuming. In this talk, we’ll kick things off by taking an audience-sourced ingredient list and asking a large language model to whip up a fresh htmlwidget. Then we’ll plate up a version we prepared earlier - also model-generated - but chopped, seasoned, and finished with our own touches. Along the way, we’ll explore how LLMs can assist in crafting htmlwidgets that reflect your flavour of R - from tidy eval to package structure - rather than sticking to a bland house style. For updates and revisions to this article, see the original post