The recent advancements in open-source AI models have sparked an engaging dialogue in the medical community about their potential to rival proprietary counterparts in diagnosing complex clinical cases. A National Institutes of Health (NIH)-funded study, led by researchers at Harvard Medical School,
When a routine investigation by New Zealand authorities revealed alarming gaps in the protocols for managing health data, the country found itself grappling with an urgent and complex challenge. In an era where data breaches are becoming increasingly frequent and sophisticated, the protection of
AI is revolutionizing precision and personalized oncology care by enabling more accurate diagnoses, predicting patient outcomes, and tailoring treatments to individual needs. Through advanced algorithms and machine learning, AI can analyze vast amounts of data, including medical records, genetic
Precision Medicine (PM), also known as personalized medicine, tailors medical treatments to individual characteristics, specifically focusing on genetic profiles. The intersection of PM and Artificial Intelligence (AI) is accelerating the adoption and effectiveness of precision medicine, addressing
Digital health technologies, including artificial intelligence, analytics, dashboards, web portals, mobile applications, virtual care, and wearables, hold transformative potential for diagnosis, treatment, and care management. However, their successful implementation and uptake in real-world
The landscape of clinical trials is on the brink of a significant transformation, driven by the integration of Real World Data (RWD). By 2025, the use of RWD is expected to revolutionize the way clinical trials are conducted, offering new opportunities for efficiency, accuracy, and patient-centric
