AIMC Topic: Biomarkers

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Engineering nonlinear epileptic biomarkers using deep learning and Benford's law.

Scientific reports
In this study, we designed two deep neural networks to encode 16 features for early seizure detection in intracranial EEG and compared them and their frequency responses to 16 widely used engineered metrics to interpret their properties: epileptogeni...

A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND: The three core pathologies of Alzheimer's disease (AD) are amyloid pathology, tau pathology, and neurodegeneration. Biomarkers exist for each. Neurodegeneration is often detected by neuroimaging, and we hypothesized that a voxel-based dee...

Utility based approach in individualized optimal dose selection using machine learning methods.

Statistics in medicine
The goal in personalized medicine is to individualize treatment using patient characteristics and improve health outcomes. Selection of optimal dose must balance the effect of dose on both treatment efficacy and toxicity outcomes. We consider a setti...

The role of artificial intelligence in paediatric neuroradiology.

Pediatric radiology
Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping...

Verhulst map measures: new biomarkers for heart rate classification.

Physical and engineering sciences in medicine
Recording, monitoring, and analyzing biological signals has received significant attention in medicine. A fundamental phase for understanding a bio-system under various conditions is to process the corresponding bio-signal appropriately. To this effe...

Assessment of a novel deep learning-based marker-less motion capture system for gait study.

Gait & posture
BACKGROUND: Marker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not bee...

Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson's Diseases and Improving the Disease Classification Using Support Vector Machine.

BioMed research international
BACKGROUND: Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the ma...

Using Artificial Intelligence to Better Predict and Develop Biomarkers.

Heart failure clinics
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, tr...

Update on risk factors and biomarkers of sudden unexplained cardiac death.

Journal of forensic and legal medicine
Sudden cardiac death (SCD) accounts for approximately 15%-20% of all deaths worldwide, the causes of which are mainly structural heart diseases. However, SCD also occurs in patients without major cardiac structural abnormalities due to electrophysiol...