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CTG Analysis Improved with AI Solutions
Practical Solutions and Value:
Cardiotocography (CTG) is a method to monitor fetal heart rate and contractions during pregnancy, aiding in early complication detection.
Interpreting CTG recordings can be subjective, leading to errors; Google’s deep learning model, CTG-net, provides an objective approach.
Using a convolutional neural network, CTG-net analyzes data to predict fetal hypoxia, improving accuracy and reducing misdiagnosis risks.
Models trained with objective pH data outperform those using subjective Apgar scores, showcasing the importance of accurate labels.
The model’s adaptability to different clinical settings enhances fetal monitoring, emphasizing the potential of AI in healthcare.
Value for Businesses:
AI can redefine workflows by automating tasks and improving decision-making processes.
Automation opportunities can be identified through key customer interactions that benefit from AI.
Setting measurable KPIs ensures AI initiatives drive meaningful business outcomes.
Choosing AI solutions tailored to specific needs and gradually implementing them enhances operational efficiency.
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