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AI models that use data where it exists rather than centralizing it require stronger privacy and security measures. Introducing the RoPPFL framework. Federated learning marks a milestone in enhancing ...
As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.
Dementia poses an increasing global health challenge, and the introduction of new drugs with diverse activity profiles ...
The Great Power Competition is no longer confined to traditional warfare. It plays out in data, algorithms and artificial intelligence (AI). As adversaries weaponize misinformation and cyber attacks ...
One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...
Danske Bank, Credit Suisse, Santander Bank UK, USAA Federal Savings Bank and Wells Fargo have all been subjected to significant fines, collectively amounting to about $2.2 billion, for various ...
Not only can federated learning reduce costs, but it can also increase the effectiveness of anti-money-laundering, say Gary Shiffman, Shelly Liposky and Rick Hamilton. The financial crimes compliance ...
Building External Control Arms From Patient-Level Electronic Health Record Data to Replicate the Randomized IMblaze370 Control Arm in Metastatic Colorectal Cancer Building well-performing machine ...
From target identification and molecular design to patient stratification and clinical trial optimization, artificial intelligence (AI) is showing remarkable promise in accelerating drug discovery and ...
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