The integration of Artificial Intelligence (AI) into healthcare is transforming diagnosis, treatment planning, medical imaging, and personalized medicine. However, the rapid integration of AI in healthcare brings both potential benefits and significant risks, such as bias, inequity, and safety concerns. To address these challenges, the Coalition for Health AI (CHAI) created a comprehensive Assurance Standards Guide. Published in June 2024, these standards were developed by leading experts in AI, healthcare, and ethics to ensure AI technologies are reliable, safe, and equitable.

Imagine a world where predicting disease, tailoring treatments, and improving patient outcomes are no longer aspirational goals but everyday realities. The field of genomics holds this potential and is modernizing medicine in ways we could only dream of a decade ago. Public access to genomics data is transforming fields like artificial intelligence (AI), biotechnology, and drug discovery. Decode Health is leveraging publicly available resources to mine a wide range of multiomics and clinical data sources efficiently, developing a best-in-class approach to discover new solutions for detecting, monitoring, and treating diseases more effectively.

This article is written in response to "AI in Pharma: The Growing Number of Pharmaceutical Use Cases" by Nick Wichert of High Alpha Innovation

Summary: Decode Health has built a mature AI/ML platform to accelerate clinical decision-making and population health analytics solutions. Check out the article below to learn more about recent collaborative efforts with a global pharmaceutical company and leading technology firm to better detect disease and identify patients at risk of high-cost events using predictive approaches in oncology and autoimmune disease.

At Decode Health, we empower the healthcare industry to implement and leverage artificial intelligence (AI) approaches, including machine learning, across a wide range of clinical applications. Data quality is paramount, especially when utilizing large, disparate datasets to address complex diseases. Decode has developed a platform that ensures the precision and reproducibility of insights and results from diverse data sources. The platform features a robust quality control (QC) framework that optimizes the efficiency and accuracy of biomarker discovery. Check out the article below to learn how our technology accelerates the biomarker discovery R&D process, widens the impact of personalized medicine, and unlocks new insights to fuel better ways to diagnose and treat patients.

Decode Health deployed its biomarker discovery platform, incorporating machine learning, to provide new insights into multiple sclerosis (MS) and neuromyelitis optica (NMO). The Decode platform identified disease-specific RNA biomarkers and connections between RNA expression [read more...]

For decades, healthcare and policy leaders have developed plans to reduce federal healthcare spending, which reached $4.3 trillion in 2021. Given recent economic shifts globally and domestically, finding solutions to mitigate healthcare costs has become even more important. Few sustainable solutions exist, and additional, more complex healthcare issues continue to emerge.

Last week’s fifth annual HLTH conference in Las Vegas was the biggest and boldest yet. The event was overflowing with interesting information and innovative ideas that push to define healthcare for the next decade. Many of the topics discussed tie directly to the work we do at Decode Health. Here are our team’s takeaways.

Autoimmune diseases, such as multiple sclerosis (MS), ulcerative colitis, Crohn’s disease, and rheumatoid arthritis, are complex diseases that affect over four million people in the United States and cost the healthcare system over $90 billion [read more...]