aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...
Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Idiopathic pulmonary fibrosis remains a hard-to-treat lung disease with limited effective drugs. A recent study in Engineering used machine learning ...
Abstract: Weather conditions directly affect sectors such as agriculture and transport. With climate change, unpredictability is increasing and traditional calculation methods may not be sufficient.
Text classification is one of the most fundamental tasks in natural language processing (NLP) and applied artificial intelligence. Many real-world applications require systems that can automatically ...
Abstract: Industrial noise classification plays a crucial role in equipment health monitoring and predictive maintenance, yet existing methods suffer from inadequate feature extraction, limited ...
Text classification plays a critical role in numerous natural language processing applications, yet limited work has addressed the unique linguistic structure of African languages such as Kiswahili.
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 = ...
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree ...
The modern digital era necessitates instantaneous automated categorisation techniques due to the increasing growth of unstructured textual data from documents, reviews, and social media as well as ...
The data acquisition methods are becoming increasingly diverse and advanced, leading to higher data dimensions, blurred classification boundaries, and overfitting datasets, affecting machine learning ...