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arXiv Machine Learning By Pablo Ramirez Amador

Artificial Intelligence Algorithms for the Detection of Pathologies Related to Lung Cancer through Image Analysis using Convolutional Neural Networks and Data Augmentation: a systematic mapping of the literature

Read the original on arXiv Machine Learning →

The article reviews recent applications of artificial intelligence and deep learning, particularly convolutional neural networks with transfer learning and data augmentation, for detecting lung cancer in medical images. It surveys 96 studies from 2015 onward, highlighting high sensitivity and specificity achieved by these methods. The authors also identify challenges such as data standardization, model explainability, patient privacy, and ethical concerns that must be addressed before clinical deployment.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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