US-based AI solutions provider Zscale Labs has introduced Neuromorphic AI, its latest medical technology to enhance diagnostic accuracy in medical imaging.
Neuromorphic AI is an AI-powered tool designed for multi-label Chest X-ray classification.
According to Zscale, accurate and timely diagnosis is critical for respiratory conditions.
Neuromorphic AI leverages the company’s Hyperdimensional Computing (HDC) and deep learning to help healthcare providers diagnose multiple chest conditions from X-ray images.
Zscale said its cognitive AI system incorporates a complex subthalamic nucleus (STN) that dynamically adjusts and transforms input images to enhance image recognition.
The system mirrors human visual attention, focusing on the most relevant parts of an X-ray, to provide enhanced accuracy and reliability.
Zscale Labs said: “Our proprietary encoder, integrated with cutting-edge Hyperdimensional Computing (HDC) technology, provides a robust mechanism for extracting and processing features from X-ray images.
“This brain-inspired approach captures intricate details crucial for precise multi-label classification, operating in a high-dimensional space for enhanced pattern cognition.”
Neuromorphic AI features advanced technical capabilities, including multi-label classification, focal loss optimisation, and adaptive learning rate.
Zscale said that its AI model can identify multiple possible conditions from a single X-ray image, offering a comprehensive analysis of the patient’s respiratory health.
The solution employs an advanced Focal Loss function to address class imbalance issues that commonly plague medical datasets, ensuring high accuracy across all condition types.
Its training process uses adaptive learning rate techniques, optimising the model’s performance and convergence during the learning phase, said the AI solutions provider.
Also, the AI model is designed for rapid, real-time analysis of X-ray images, augmenting medical professionals’ quick decision-making in clinical settings.
Its neural network architecture is scalable, enabling easy adaptation to larger datasets and more complex classification tasks as needed.
Zscale Labs said: “The AI model has been meticulously trained on diverse datasets of chest X-rays, covering a wide range of respiratory conditions.
“This extensive training ensures high accuracy in multi-label classification, thus supporting well-informed and quickly generated personalised treatment plans for your patients’ predictive healthcare strategies.”
