Abstract: This review paper introduces an advanced deep-learning method to tackle imbalanced medical datasets, frequently arising due to limited data availability and privacy restrictions in ...

However, the extent to which these types of data have been incorporated into deep learning (DL) models has not been examined. Objective: This systematic review aims to describe the use of sequential ...

Abstract: The integrity of water quality data has an important impact on water quality prediction and analysis, so it is necessary to impute the missing values in the data. However, at present, most ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of payments. We live in a world where machines can understand speech, recognize faces, and even generate ...

Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...

Claude writes confident MATLAB code, but it sometimes makes up function names that don't exist in R2025b. These skills fix that. They give Claude a quick-reference of tricky APIs, deprecated functions ...

The Chat feature of Google AI Studio allows users to interact with Gemini models in a conversational format. This feature can make everyday tasks easier, such as planning a trip itinerary, drafting an ...

Nothing dominates the technology news cycle more than AI in its many forms, and for data professionals, the discussion often mentions deep learning. But what are the use cases for this technology? How ...

Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.

A few years back, one of us sat in a school district meeting where administrators and educators talked about the latest student achievement results. The news was not good. Students’ test scores hadn’t ...