Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, enabling researchers to process large volumes of environmental data and satellite ...

Objective Geriatric patients often face issues related to polypharmacy and adverse drug events. Re-evaluating prescribed medications and considering deprescribing is critical. Medication discrepancies ...

Medical image classification is a critical task where precision is paramount. A false negative can delay life-saving treatment, while a false positive can lead to unnecessary stress and procedures.

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

Abstract: This paper presents a novel sleep/wake classification method based on heart rate and pulse oximetry, using logistic model with derived dynamic time warping and correlation features ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...

ABSTRACT: A degenerative neurological condition called Parkinson disease (PD) that evolves progressively, making detection difficult. A neurologist requires a clear healthcare history from the ...

In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing pulmonary disease ...

When it comes to artificial intelligence, more intensive computing uses more energy, producing more greenhouse gases. By Sachi Kitajima Mulkey Graphics by Harry Stevens From uninvited results at the ...