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5th Edition of

International Public Health Conference

March 19-21, 2026 | Singapore

Neural Networks

Neural Networks

Deep learning techniques are based on neural networks, sometimes referred to as artificial neural networks (ANNs) or simulated neural networks (SNNs), which are a subset of machine learning. Their structure and nomenclature are modelled after the human brain, mirroring the communication between organic neurons. A node layer, which includes an input layer, one or more hidden layers, and an output layer, makes up artificial neural networks. Each node, or artificial neuron, is connected to others and has a weight and threshold that go along with it. Any node whose output exceeds the defined threshold value is activated and begins providing data to the network's uppermost layer. Otherwise, no data is sent to the network's next tier.

Committee Members
Speaker at International Public Health Conference 2026 - Gregory S Anderson

Gregory S Anderson

Thompson Rivers University, Canada
Speaker at International Public Health Conference 2026 - David John Wortley

David John Wortley

World Lifestyle Medicine Education Services, United Kingdom
Speaker at International Public Health Conference 2026 - Bob Esquerre

Bob Esquerre

Esquerre Fitness Group International, United States
IPHC 2026 Speakers
Speaker at International Public Health Conference 2026 - Amelia Burke Garcia

Amelia Burke Garcia

NORC at the University of Chicago, United States
Speaker at International Public Health Conference 2026 - Rafaela Julia Batista Veronezi

Rafaela Julia Batista Veronezi

Physiotherapist, Neuroscientist & Public Health Educator, United States
Speaker at International Public Health Conference 2026 - Roman Sharnuud

Roman Sharnuud

University of Tennessee, United States
Speaker at International Public Health Conference 2026 - Edmond Kubi Appiah

Edmond Kubi Appiah

Drexel University, United States

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