Automatic label checking: The missing step in making medical AI reliable

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
EurekAlert!

Maize-IRNet: a deep-learning “field scorer” for tassel anthers and ear seed set

A research team has developed an AI-based approach to streamline the evaluation of maize haploid fertility restoration, a key bottleneck in double haploid (DH) breeding.
Learn With Jay on MSNOpinion

Deep learning regularization: Prevent overfitting effectively explained

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
eWeek

Types of AI Models: A Deep Dive into AI Architecture

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
EurekAlert!

From time series to a single snapshot: A smarter way to track wheat growth in real time

A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...