Nature

Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks

In an era marked by exponential data growth and pervasive digital connectivity, understanding the intricate structure of networks has become a critical challenge across various domains. Whether ...
Law

Training Alone Is Not Enough: Lessons From 'Recentive' and USPTO AI Examples on Patent Eligible Machine-Learning Claims

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
Forbes

How AI, Data Science, And Machine Learning Are Shaping The Future

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Nature

Using causal machine learning and real world data to improve dose response decision making for secukinumab in psoriatic arthritis

Personalized treatment in psoriatic arthritis (PsA) remains challenging, particularly in guiding dose escalation decisions. We applied a causal machine learning framework to real-world data from the ...