Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made,…
Brain Informatics Template
Write in a clean editor, then format for Brain Informatics in one click — DocuGuru applies the official Springer Nature template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
About the Brain Informatics format
Brain Informatics is a peer-reviewed journal published by Springer Nature, covering EEG and Brain-Computer Interfaces, Functional Brain Connectivity Studies, Neural dynamics and brain function.
| Publisher | Springer Nature |
|---|---|
| Reference style | Numbered (Springer Basic) Numbered — [1], [2] in the text 1. Smith A, Jones B, Lee C (2023) A representative article title. Brain Informatics 12:45–58
Formats any DOI in Brain Informatics style. No sign-up. |
| Publishes research in | EEG and Brain-Computer Interfaces Functional Brain Connectivity Studies Neural dynamics and brain function Blind Source Separation Techniques Dementia and Cognitive Impairment Research |
| ISSN | 2198-4018 |
| Citation impact (2-yr) | 9.73 |
| h-index | 48 |
| i10-index | 176 |
| Total citations | 10,397 |
| Article processing charge | $969 |
| Open access | Yes |
| Top institutions publishing here | University of Southern Queensland |
| Journal website | braininformatics.springeropen.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Papers published in Brain Informatics per year
Citation impact of Brain Informatics by publication year
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Most-cited papers in Brain Informatics
Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing 'atypical' (compared to…
The identification, segmentation and detection of infecting area in brain tumor MRI images are a tedious and time-consuming task. The different anatomy structure of human body can be visualized by an image processing concepts. It is very difficult to have vision about the abnormal structures of human brain using simple imaging techniques. Magnetic resonance imaging…
Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research.…
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human organs and generate signals. The monitoring of these brain signals is commonly done using Electroencephalogram (EEG) and Electrocorticography (ECoG) media. These signals…