Related papers: NSTRI Global Collaborative Research Data Platform
Decentralized Health Intelligence Network (DHIN) extends the Decentralized Intelligence Network (DIN) framework to address challenges in healthcare data sovereignty and AI utilization. Building upon DIN's core principles, DHIN introduces…
Stanford Medicine is building a new data platform for our academic research community to do better clinical data science. Hospitals have a large amount of patient data and researchers have demonstrated the ability to reuse that data and AI…
Secure and scalable data sharing is essential for collaborative clinical decision making. Conventional clinical data efforts are often siloed, however, which creates barriers to efficient information exchange and impedes effective treatment…
Individual health data is crucial for scientific advancements, particularly in developing Artificial Intelligence (AI); however, sharing real patient information is often restricted due to privacy concerns. A promising solution to this…
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science…
Recent emergence of electronic culture uplifts healthcare facilities to a new era with the aid of wireless sensor network (WSN) technology. Due to the sensitiveness of medical data, austere privacy and security are inevitable for all parts…
English based datasets are commonly available from Kaggle, GitHub, or recently published papers. Although benchmark tests with English datasets are sufficient to show off the performances of new models and methods, still a researcher need…
Electronic Health Records (EHRs) store sensitive patient information, necessitating stringent access control and sharing mechanisms to uphold data security and comply with privacy regulations such as the General Data Protection Regulation…
One of the biggest challenges of building artificial intelligence (AI) model in the healthcare area is the data sharing. Since healthcare data is private, sensitive, and heterogeneous, collecting sufficient data for modelling is exhausting,…
Objective: Health-related data being collected by smartphones offer a promising complementary approach to in-clinic assessments. Here we introduce the JTrack platform as a secure, reliable and extendable open-source solution for remote…
The Global Research infrastructure (GRI) is made up of the repositories and organizations that provide persistent identifiers (PIDs) and metadata for many kinds of research objects and connect these objects to funders, research…
The electronic health record (EHR) targets the systematized collection of patient-specific electronically-stored health data. Currently the EHR is an evolving concept driven by ongoing technical developments and open or unclear legal issues…
Healthcare AI holds the potential to increase patient safety, augment efficiency and improve patient outcomes, yet research is often limited by data access, cohort curation, and tooling for analysis. Collection and translation of electronic…
Digital twin (DT) technology holds immense potential for transforming healthcare systems through real-time monitoring, predictive analysis, and agile interventions to support various decision-making needs. However, its successful…
This paper investigates the optimal locations and capacities of hospital expansion facilities under uncertain future patient demands, considering both spatial and temporal correlations. We propose a novel two-stage distributionally robust…
Electronic Health Record (EHR) has become an essential tool in the healthcare ecosystem, providing authorized clinicians with patients' health-related information for better treatment. While most developed countries are taking advantage of…
During the last decade, we have witnessed a sustained growth of South Korea's research output in terms of the world share of publications in the Science Citation Index database. However, Korea's citation performance is not yet as…
We present ClinicalTrialsHub, an interactive search-focused platform that consolidates all data from ClinicalTrials.gov and augments it by automatically extracting and structuring trial-relevant information from PubMed research articles.…
Generative Artificial Intelligence (GenAI) is taking the world by storm. It promises transformative opportunities for advancing and disrupting existing practices, including healthcare. From large language models (LLMs) for clinical note…
Self-supervised learning (SSL) has emerged as a promising paradigm in medical imaging, addressing the chronic challenge of limited labeled data in healthcare settings. While SSL has shown impressive results, existing studies in the medical…