About the Neural Networks Session
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.
Topics Covered in Neural Networks
Network architectures and layer design
Activation functions and weight optimisation
Training, backpropagation and loss functions
Convolutional and recurrent network models
Model generalisation and overfitting control
Neural networks for health data applications
Featured Speakers — Neural Networks 2027
Speaker lineup for this track will be announced soon.
Browse all speakers →Recent Research Presented at Neural Networks Sessions
Selected abstracts from this track will be published here.
Related Scientific Sessions at IPHC 2027
Why Attend the Neural Networks Conference 2027
Earn CPD Credit
Sessions are CPD-accredited; certificates issued to every registered delegate within two weeks of the conference.
Present Your Research
Oral and poster slots for original Neural Networks work, reviewed by the scientific committee.
Network Globally
Meet public health researchers, educators, and policy leaders from around the world across three days.
Publish & Get Indexed
Accepted abstracts appear in the indexed conference proceedings with a citable DOI.
Learn from Keynotes
Plenary lectures from leading voices shaping Neural Networks research and practice.
Hybrid Flexibility
Attend in person in Singapore or join virtually — same programme, same certificate.
Join IPHC 2027 for the Neural Networks track
Oral and poster slots for your work — in person in Singapore or online. Not presenting? Attend as a delegate to learn from the field.
Neural Networks Conference 2027 — FAQs
What is the Neural Networks track at IPHC 2027?
The Neural Networks track is a dedicated stream within IPHC 2027 covering the latest research, innovation, and best practice in Neural Networks. It brings together researchers, educators, and practitioners for oral presentations, posters, and discussion.
Who should attend the Neural Networks sessions?
Public health researchers, practitioners, epidemiologists, educators, doctoral students, and policy leaders with an interest in Neural Networks are all welcome — whether presenting or attending.
Can I present my research in the Neural Networks track?
Yes. Submit an abstract for oral or poster presentation. All submissions are peer-reviewed by the scientific committee; accepted abstracts appear in the indexed proceedings.
Is virtual attendance available for Neural Networks sessions?
Yes. IPHC 2027 is a hybrid conference — attend the Neural Networks track in person in Singapore or join live online, with on-demand access afterward.
Join the IPHC 2027 delegation
Singapore · March 15–17, 2027· Hybrid · in-person & virtual
Attend without presenting.