This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

The healthcare sector is increasingly reliant on digital technologies, demonstrating a strong commitment to using advanced tools for better patient care and more efficient data management. However, ...

As an HR or talent acquisition leader, you are leading a crucial transformation. Nearly every American corporation is now harnessing technology to enhance their hiring processes, and this shift has ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Many companies are searching for tools to help them hire diverse, productive workforces. Even if diversity is not the main hiring goal, they may want to ensure they’re not overlooking talented ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

Chatbots Kill: In 2017, the Pentagon established Project Maven to apply machine learning (ML) technology to identify targets in real-time combat situations. The program has now seemingly been turned ...