Tech Xplore

Machine-readable dataset speeds environmental review drafting tasks

An innovative partnership has yielded powerful new tools to help federal agencies rapidly synthesize complex data, historical ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

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 develop new 'emotionally aware' model for classifying mental health conditions

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
IEEE

Rainfall Classification Using Machine Learning Algorithms on Data Mining Platforms

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.
IEEE

Multi-Dimensional Feature Extraction and Classification Method for Industrial Noise Integrating Wavelet Transform and Machine Learning

Abstract: Industrial noise classification plays a crucial role in equipment health monitoring and predictive maintenance, yet existing methods suffer from inadequate feature extraction, limited ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

In many countries, patients with headache disorders such as migraine remain under-recognized and under-diagnosed. Patients affected by these disorders are often unaware of the seriousness of their ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.