πŸ“š Bibliography: Neural Networks and Perceptron

Neural Network Fundamentals

ResourceType/FocusLanguageAccess
scikit-learn: Neural network modelsTechnical documentation on Multi-layer Perceptron (MLP) and classification/regression with neural networksENOnline
Wikipedia: Artificial neural networkIntroduction to artificial neural networks, history and architectureENOnline
3Blue1Brown: Neural NetworksVisual video series on how neural networks workENYouTube
Nielsen, M. A. (2015). Neural Networks and Deep LearningFree online book on neural network fundamentalsENOnline

Perceptron

ResourceType/FocusLanguageAccess
Wikipedia: PerceptronHistory of Rosenblatt's perceptron and mathematical foundationsENOnline
Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain"Original perceptron paperENArticle
MIT: Introduction to Neural NetworksMIT course on neural networksENOnline
Minsky, M., & Papert, S. (1969). PerceptronsClassic book on perceptron limitationsENBook

Backpropagation Algorithm

ResourceType/FocusLanguageAccess
Stanford UFLDL: Backpropagation AlgorithmStanford tutorial on backpropagationENOnline
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). "Learning representations by back-propagating errors"Seminal paper on backpropagationENArticle
Gradient Descent, How Neural Networks Learn3Blue1Brown video on gradient descentENYouTube
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep LearningChapter 6: Deep Feedforward NetworksENBook

Medical Applications of Neural Networks

ResourceType/FocusLanguageAccess
Nature: Deep learning in medical imagingReview on deep learning for medical diagnosisENArticle
NIH: Neural networks for disease diagnosisNeural network applications in disease diagnosisENArticle
Diabetic Retinopathy DetectionKaggle dataset and competition on diabetic retinopathy detectionENOnline
WHO: AI for healthWHO perspective on AI in healthEN/ESOnline

Note: All links have been verified and are accessible online. For access to scientific articles, check your university library, Google Scholar or platforms like arXiv.