Abstract: This research aims to explore the use of modern complex defensive machine learning algorithms in the provision of predictive analytics for health improvement. Incorporating electronic health ...

Programming efficient asynchronous systems is challenging because it can often be hard to express the design declaratively, or to defend against interleaving-dependent bugs such as data races and ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

Anthropic has been testing how far AI agents can go by letting one run a real vending machine inside the Wall Street Journal newsroom – but it quickly lost a lot of money. The experiment, documented ...

The tensile testing machine described here is a fully open-source device designed to determine the mechanical tensile strength of test specimens. At its core, it uses a single-board computer ...

Introduction: Diagnosis of active Mycobacterium tuberculosis (Mtb) infection relies on clinical symptoms, imaging, and molecular testing, but these methods are often costly and slow. Consequently, ...

Abstract: Modern image recognition has experienced dramatic improvements because of Machine Learning and Deep Learning algorithms together. This study investigates CNNs and SVMs for recognition ...

We introduce PaCoRe (Parallel Coordinated Reasoning), a framework that shifts the driver of inference from sequential depth to coordinated parallel breadth, breaking the model context limitation and ...