AI in healthcare and medical research
Transforming patient outcomes and research
Artificial Intelligence (AI) is rapidly transforming healthcare by unlocking new possibilities in patient care, clinical research, and medical insights.
An introduction to AI in healthcare
From predicting disease outcomes to enhancing personalised medicine, AI significantly improves healthcare efficiency when used responsibly. Real-world successes include AI-powered diagnostics improving the early detection of cancer, predictive analytics reducing hospital readmissions, and personalised medicine applications tailoring treatments precisely to individual patient needs.
Benefits and challenges of AI in medical research
AI offers powerful benefits such as rapid clinical data analysis, improved diagnostic accuracy, and accelerated discovery of treatments. However, using AI also raises challenges, including data protection issues, patient privacy, algorithmic bias, and ethical considerations, making responsible implementation essential.
Artificial Intelligence Opportunities
Learn how the Aridhia DRE fully integrates AI/ML solutions into Workspaces environments making it an ideal choice for future AI-based precision dosing strategies.
AI and data Protection: Why it matters
As the growth in AI applications in the healthcare space continues to rapidly increase it is more important than ever to safeguard patient data and ensure their privacy is not impacted by use of AI.
Protecting patient privacy in healthcare AI
Patient privacy is critical when integrating AI in healthcare. Cloud-based AI systems can pose significant risks due to potential loss of data privacy, unintended exposure of sensitive prompts, or misuse in model training. The offline AI capabilities of our Trusted Research Environment (Enterprise and SaaS versions) directly address these concerns, keeping all patient data, prompts and outputs secure and fully within your control.
AI and regulatory compliance (GDPR & HIPAA)
Healthcare organisations face strict regulatory requirements like GDPR in the EU and HIPAA in the US, making online AI platforms challenging due to data privacy and security risks. Our secure, offline AI capabilities solve these issues by ensuring sensitive patient data and AI prompts never leave your trusted environment. Additionally, our flexible Digital Research Environment infrastructure adapts seamlessly to any jurisdiction, enabling secure, compliant collaboration and data federation across multiple regulatory landscapes.
The Aridhia DRE
Our Digital Research Environment has been developed for over 10 years to be adaptable to the everchanging technological requirements that face medical research and healthcare. The emegence of AI and its integration into our DRE will enhance the tools avialable to researchers and improve patient outcomes.
Secure, compliant AI solutions using offline AI
Our DRE enables customers to run cutting edge offline Large Language Models (LLMs) securely. Removing cloud dependency, offline LLMs significantly enhance patient privacy, regulatory compliance, and data security – your prompts, data, and outputs all stay securely yours within the environment as all times. We’ve successfully delivered secure analytics solutions for use-cases including clinical note summarisation, biomarker identification, and precision medicine analytics, all within trusted, compliant environments.
Secure, Federated Research Capabilities
Our Digital Research Environment (DRE) integrates AI seamlessly to enable secure, sophisticated medical research applications. From personalised medicine to real-world data studies and biomarker identification, our Trusted Research Environment ensures robust compliance and privacy. Uniquely positioned to federate data securely across jurisdictions, our solution promotes global collaboration and innovation without compromising regulatory standards.
Using offline LLMs in a TRE – A case study
Learn how offline LLM’s can work securely from within a Trusted Research Environment in a case study using breast cancer data.