Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
UPI

Lottery vending machine error leads Ohio woman to more than $50,000

Nov. 10 (UPI) --An Ohio woman pushed the wrong button on an Ohio Lottery vending machine and set off a series of events that ended with her winning over $50,000. The Minister resident, named Nancy, ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
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 ...
GitHub

MACHINE LEARNING FOR QUANTUM NOISE REDUCTION USING DENSITY MATRIX

Quantum computation has the potential for exponential speedup of classical systems in some applications, such as cryptography, simulation of molecular behavior, and optimization. Nevertheless, quantum ...
Frontiers

Analysis of the association between dietary sodium intake and cognitive function: a NHANES-based machine learning study and animal experimental validation

Background: Sodium intake is undoubtedly essential for normal bodily function, but it is an important public health concern when intake exceeds dietary requirements. With salt intake exceeding ...
EurekAlert!

AI meets quantum: Machine learning advances estimation and control of quantum systems

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...
IEEE

Machine Learning-Based Error Detection and Function Approximation for Reliable Computing

Abstract: Ensuring reliability in modern computing systems requires efficient and accurate error detection mechanisms. This paper explores a machine learning based ...