Oracle’s AI-First Healthcare Approach
Oracle Health is strategically positioning itself at the forefront of the healthcare AI revolution, leveraging its comprehensive data and technology infrastructure to outpace competitors in the rapidly evolving healthcare market. The…
Original, trusted content isn't just for SEO—Julia Goebel says quality real-world data is key to better AI outcomes in healthcare.🎥 Full clip: https://www.healthcareittoday.com/2025/07/15/komodo-health-talks-real-world-data-and-the-importance-of-high-quality-data/#KomodoHealth #healthttech…
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The use of synthetic data to augment real-world data in healthcare can ensure AI models perform more accurately, and fairly across subgroups. By examining a parallel case study of NHS England’s care.data platform, this…
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Early prediction of disability progression in multiple sclerosis (MS) remains challenging despite its critical importance for therapeutic decision-making. We present the first systematic evaluation of personalized federated learning (PFL) for 2-year MS disability progression…
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What You Should Know:
– Flatiron Health, a leading healthtech company dedicated to improving cancer care and advancing research using real-world data (RWD), today announced that its international oncology research network has tripled in size…
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The widespread adoption of real-world data has given rise to numerous healthcare-distributed research networks, but multi-site analyses still face administrative burdens and data privacy challenges. In response, we developed a Collaborative One-shot Lossless Algorithm…
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Real-world data (RWD) from electronic health records and digital health databases present unique opportunities to study causal effects in healthcare. While Difference-in-Differences (DiD) analysis is widely used for such analyses, it can be biased…
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In this interview, Julia Goebel, Chief Marketing Officer at Komodo Health, surveys the current state of health care data, the importance of high-quality data in the deployment of new technologies such as AI, and…
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Clinical insights from real-world data often require aggregating information from institutions to ensure sufficient sample sizes and generalizability. However, patient privacy concerns only limit the sharing of patient-level data, and traditional federated learning algorithms,…
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Subspecialty knowledge barriers have limited the adoption of large language models (LLMs) in oncology. We introduce Woollie, an open-source, oncology-specific LLM trained on real-world data from Memorial Sloan Kettering Cancer Center (MSK) across lung,…
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