Machine learning accurately distinguished peanut allergy from peanut sensitisation, highlighting its potential to support ...

Explainable Artificial Intelligence (XAI) seeks to render the operation and decisions of complex machine learning systems transparent and interpretable to users, regulators and other stakeholders. As ...

Artificial intelligence may be able to do more than predict what happens after prostate cancer surgery; it can also help ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

Lung cancer (LC) is a leading cause of cancer-related mortality in the United States. Accurate prediction of LC mortality rates is crucial for guiding targeted interventions and addressing health ...

Across the UK, financial institutions are using machine learning models to make decisions that affect millions of people. These decisions include credit approvals, fraud alerts, investment ...

Using a real-world, nationwide electronic health record–derived deidentified database of 38,048 patients with advanced NSCLC, we trained binary prediction algorithms to predict likelihood of 12-month ...

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights—including a model-estimated probability score for ...

Tech companies have developed machine learning models and algorithms expeditiously in recent years. Those familiar with this technology likely remember a time when, for instance, bank personnel and ...

Enabled Intelligence (EI), the leader in high-precision AI data labeling, and Seekr, the leader in explainable, defensible AI, today announced a partnership to bring greater speed and efficiency to ...

Exercise training is a cornerstone of cardiac rehabilitation (CR) for patients with coronary artery disease (CAD), and ...