Author: Patricia Buendia
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Part 2: Enhancing EHR Data Quality: Key Findings from Recent Studies
This post is Part 2 of our 2-part series on recent research studies looking at EHR data quality. Part 1 presented 3 studies from 2025, and Part 2 presents 2 more recent studies and a proposed technological shift that avoids the pitfalls of traditional data pipelines. Study #4. Interoperability Remains a Pain Point While previous…
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Part 1: Reactive vs. Proactive: The High Cost of Unvalidated EHR Data
Electronic Health Records were meant to be the backbone of modern healthcare and AI clinical prediction system. Instead, the 2025 research landscape paints a sobering picture. EHR data is incomplete, inconsistent, and often wrong at a scale that threatens clinical research, AI development, and even day‑to‑day patient care. Across multiple new studies, a consistent theme…
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Autonomous Agents Visiting Data
The Google AI Agents Intensive Course (5DGAI) debuted in March 2025 (First 5DGAI) and returned in November 2025 (second 5DGAI), offering developers a front-row seat to the rapid evolution of agentic systems. The First 5DGAI course focused on foundational skills: writing prompts, training agents, customizing them using Retrieval-Augmented Generation (RAG), and deploying them via MLOps.…
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Data Visiting and the Future of Inclusive Biomedical Research
In the age of AI-driven discovery, biomedical research is undergoing a quiet revolution—one that’s not just about faster algorithms or bigger datasets, but about rethinking how we access and share data across borders, institutions, and communities. The Geographies of Trust report published on Zenodo offers a timely exploration of this shift, spotlighting technologies that respect…
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Data Visiting in Patient-Controlled Health Wallets
Back in 2019, we ran a project we called “Symphony” alongside three blockchain pioneers, driven by a bold vision: to empower patients with full control over their health data through a personal data wallet. The goal was to let individuals decide who could access their records — and even monetize that access if desired. We…
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FAIR Data Trains
The FAIR Data Train is a data analysis approach that combines two key elements: As described in the LIFES Networking Meeting from December 2024: The FAIR Data Train approach was introduced as a domain-agnostic system designed to enhance automated interoperability while adhering to FAIR principles. Key aspects include privacy-focused “data visiting”, foundational agreements for metadata…
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Has Generative AI Killed the PID Star? – PIDs Part 2
The role of Persistent Identifiers (PIDs) – those enduring signposts in the digital landscape – is facing a fascinating challenge from the rise of Generative AI. At a recent meeting of the Research Data Alliance (RDA) PID Interest Group, experts gathered to debate whether AI is destined to make PIDs obsolete or, conversely, to amplify…
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The PID Paradox – PIDs Part 1
The digital age has ushered in an unprecedented era for scientific discovery, promising accelerated progress through open data sharing. Yet, beneath the surface of progressive policies and sophisticated technological solutions lies a potent psychological barrier: the fear of being “scooped.” This anxiety, deeply ingrained in the competitive landscape of research can be traced back to…
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Federated Data Platforms vs. Data Visiting Technologies
What technologies and methods enable the access and analysis of sensitive data using AI/ML, while preserving data privacy and avoiding centralization? That’s the challenge federated data and data visitation technologies aim to solve. But are they the same thing? Not quite. This post will break down the key differences, explore their respective applications, and provide…
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Dataset Digital Twin in Biomedical Research
Imagine a holographic view of a patient—a Biomedical Digital Twin—reflecting their unique physiology, lifestyle, and medical history. This isn’t science fiction; it’s a rapidly evolving field transforming healthcare and research. This article explores various types of digital twins and their applications, with a focus on dataset digital twins. Types of digital twins in biomedical research…