Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment

B, an open-source AI coding model trained in four days on Nvidia B200 GPUs, publishing its full reinforcement-learning stack as Claude Code hype underscores the accelerating race to automate software ...
Frontiers

Comparative analysis of clinical feature–based machine learning models for predicting myofascial pelvic pain syndrome: a single-center retrospective study

1 Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China 2 Prenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of ...
NPR

2 Senators want to hold big tech accountable for harms caused by algorithms

Social media companies and their respective algorithms have repeatedly been accused of fueling political polarization by promoting divisive content on their platforms. Now, two U.S. Senators have ...
Wired

A New Algorithm Makes It Faster to Find the Shortest Paths

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...
Scientific American

The Internet Is Making Us Fluent in Algospeak

Every time a new slang word gets coined on the Internet, linguist Adam Aleksic is thrilled. “It’s definitely good for me in that I stay in business,” says Aleksic, who studies the origins of words and ...
Frontiers

Investigation of predictive factors for fatty liver in children and adolescents using artificial intelligence

Background: Childhood obesity is a growing problem worldwide, leading to non-alcoholic fatty liver disease (NAFLD), which is the most common liver disease in children. Liver biopsy is the gold ...
GitHub

TreeSHAP-compatible AdaBoost and RUSBoost classifiers for explainable AI on imbalanced datasets.

This package provides custom implementations of AdaBoost and RUSBoost classifiers that are compatible with SHAP's TreeExplainer, enabling fast local explanations for boosting algorithms on imbalanced ...
Marine Link

Algorithm Accountability

When the maritime trade union Nautilus International asked memberswhat they thought of AI at a forum in January, there was some positive sentiment: “We shouldn’t automatically assume there will be ...
Healio

Real-world dermatology dataset reveals flaws of some AI diagnostic algorithms

Please provide your email address to receive an email when new articles are posted on . AI algorithms to diagnose skin cancer had lower sensitivity and specificity when tested on a multimodal, ...
IEEE

A Novel AdaBoost Framework With Robust Threshold and Structural Optimization

Abstract: The AdaBoost algorithm is a popular ensemble method that combines several weak learners to boost generalization performance. However, conventional AdaBoost.RT algorithms suffer from the ...