Years ago, as she sat in waiting rooms, Maytal Saar-Tsechansky began to wonder how people chose a good doctor when they had ...

Binjumah, W. (2025) A Conceptual Model for Improving Perovskite Solar Cells Efficiency Using Machine Learning. International ...

AI and RAN Traffic Optimization Market size is expected to reach USD 27.2 bn by 2034, projected at a CAGR of 28.6% during ...

TrialTranslator uses machine learning to assess cancer RCT generalizability, revealing survival gaps for high-risk patients ...

Innovative graphene-based solar absorber design with Al, TiN, and Fe layers shows over 95 % absorbance, enhanced by machine ...

As a core course in big data analysis technology, data mining and machine learning have a relatively short history and are basically in the process of exploration. There are many problems in the ...

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed. Become skilled in Artificial Intelligence, ...

Linear regression is one of the simplest and commonly used algorithms in machine learning. It is a supervised learning technique aimed at modeling the relationship between a dependent variable and one ...

If you apply for a job, AI algorithms can be used to screen ... Machine Learning (ML) and Deep Learning (DL) algorithms can reduce road accidents through their ability to detect sleepy drivers and ...

The manufacturing process includes job fabrication in distributed blocking flowshops, job-to-product assembly on an assembling machine ... algorithms for different optimization problems. Based on this ...

These inscriptions become very visible when algorithms, using artificial intelligence models, seek to learn from the past to act in the present and project something into the future. For example, the ...