Technology Networks

Machine Learning Applications in Proteomics

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Que.com on MSN

UNT launches new artificial intelligence major to meet workforce demand

The University of North Texas (UNT) is stepping into the future with a new undergraduate major in Artificial Intelligence (AI), ...
AHA/ASA Journals

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
Opinion

India’s AI choices at the 2026 AI Impact Summit amid structural drifts in global markets

As we approach the AI Impact Summit 2026, global AI exosystems are undergoing a brutal yet necessary recalibration. Those calibrations are driven by t.
Unite.AI

Jailbreaking AI Censors Via In-Image Text

Researchers claim that leading image editing AIs can be jailbroken through rasterized text and visual cues, allowing prohibited edits to bypass safety filters and succeed in up to 80.9% of cases.
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Que.com on MSN

Kennesaw State launches new AI bachelor’s degree for fall 2026

Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
IEEE

HMM-Based Feature Extraction and Machine Learning Methods for Event Detection and Classification in Microgrids

Abstract: The increasing penetration of inverter-based distributed generation (DG) into power grids improves access to electricity and provides a significant possibility for decarbonization. However, ...
Scientific Research Publishing

Martins, A. and Astudillo, R. (2016) From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification. International Conference on Machine Learning, New ...

ABSTRACT: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...
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.
Frontiers

Medical short text classification via Soft Prompt-tuning

In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...