HYBRID EVENT: You can participate in person at Singapore or Virtually from your home or work.
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
David John Wortley
International Society of Digital Medicine (ISDM), United Kingdom
Bob Esquerre
Esquerre Fitness Group International, United States
Kyrisakos Kouveliotis
Berlin School of Business and Innovation, GermanySubmit your abstract Today
Title : Spillover at the edge: Mapping zoonotic disease risk in the wildland-urban interface
Roman Sharnuud, University of Tennessee, United States
Title : AI for good? Expanding our understanding of opinion leaders in a changing digital landscape
Amelia Burke Garcia, NORC at the University of Chicago, United States
Title : Confidence as care: Empowering under represented voices in public health leadership and community engagement
Sheena Yap Chan, The Tao of Self-Confidence, Canada
Title : Redefining eHealth literacy for the digital age: A scoping review to advance equity, engagement, and behaviour change
Comfort Sanuade, Concordia University, Canada
Title : Innovative approaches in public health leadership: Empowering communities for resilient health systems
Mohammad Kamal Hussain, Umm Al-Qura University, Saudi Arabia
Title : Assessing human exposure to key chemical carcinogens diagnostic approaches and interpretation
Vladan Radosavljevic, Military Medical Academy, Serbia