Abstract: The primary aim of this study is to assess the performance of various ML algorithms in diagnosing diabetes depending on various data preprocessing methods. Utilizing the Pima Indian Diabetes ...

Tariffs and uncertainty were already making the economy hard to read. The loss of government data during the shutdown has made the situation much worse. By Ben Casselman and Colby Smith Tariffs are at ...

Here we present example workflows to perform a large scale untargeted metabolomics LC-MS/MS data preprocessing for molecular networking analysis using GNPS. The data set is described in Nothias, L.F.

Abstract: This study is based on the application of a real-measured data preprocessing method using data augmentation techniques. In response to the scarcity of sample data in the fields of ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

Wrapping up a multi-week series on Crafting Data Personas. What are they, why are they important, and how to get started. Continuing from last week, we’re diving right into examples of personas. I ...

ABSTRACT: This paper focuses on the use of YOLOv12 for the early detection of Sexually Transmitted Infections, which are a global public health challenge. YOLOv12 is a deep-learning model released on ...

For lithologic oil reservoirs, lithology identification plays a significant guiding role in exploration targeting, reservoir evaluation, well network adjustment and optimization, and the establishment ...