Validating the reliability of AI algorithms for detecting cardiac arrhythmias in ECGs
Early detection of cardiac arrhythmia is crucial, as this common medical condition can lead to major, even fatal, complications if left undiagnosed a…
Improve AI system design for quality control industry
The transition to Industry 4.0 is a crucial issue for the manufacturing sector, and AI represents a powerful lever to accelerate this revolution. Mai…
Measure robustness of data augmentation
Does data augmentation make a neural network more robust and how to measure it? Saimple allows us to measure the robustness of a neural network thank…
Improve model robustness with data augmentation for e-commerce
With the development of online retailing, artificial intelligence is becoming increasingly important for the fashion industry. According to a report…
Detect measurement bias in deep learning models
Measurement biases can occur in any dataset and are not easy to detect. Saimple helps to detect these biases and data augmentation can be a solution…
Identify bias in cancer cells detection from ultrasounds
Cancer kills several million people each year worldwide. However, some studies [1] have shown that the date of cancer diagnosis has a significant imp…
Evaluation of model robustness for traffic sign classification
Among the current challenges facing the automotive industry, demonstrating the reliability of AI embedded systems in autonomous cars is paramount.
Detect learning bias in AI models
This use case example will help to understand what an association bias is, how to detect it and finally how to overcome the issue with Saimple. Saimp…
Improve pattern recognition in x-rays for pneumonia prediction
This use case highlights how the Saimple tool offers healthcare professionals the ability to understand the origin of the clinical decision made by t…
Detect anomalies and analyze behavior in AI through relevance
In artificial intelligence, neural networks are traditionally compared to black boxes. Explainability is therefore a fundamental issue. Indeed, for a…
