AIMC Topic: Biomarkers

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Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer.

World journal of gastroenterology
BACKGROUND: Because of the powerful abilities of self-learning and handling complex biological information, artificial neural network (ANN) models have been widely applied to disease diagnosis, imaging analysis, and prognosis prediction. However, the...

[Research progress of feature selection and machine learning methods for mass spectrometry-based protein biomarker discovery].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
With the development of mass spectrometry technologies and bioinformatics analysis algorithms, disease research-driven human proteome project (HPP) is advancing rapidly. Protein biomarkers play critical roles in clinical applications and the biomarke...

Automatic Classification and Monitoring of Denovo Parkinson's Disease by Learning Demographic and Clinical Features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Parkinson's Disease (PD) is the second most prevalent progressive neurological disorder around the world with high incidence rates for seniors. Since most symptoms are exposed in the later stages of the disease, early diagnosis of PD is essential for...

Optimal ELM-RBF model and SERS Analysis of Saliva for Classification of NS1.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Extreme Learning Machine (ELM) with Radial Basis Function (RBF) Kernel has demonstrated strong capability in pattern recognition and classification problems. NS1 is a biomarker for flavivirus related diseases, where current detection methods are seru...

2D Wavelet Scalogram Training of Deep Convolutional Neural Network for Automatic Identification of Micro-Scale Sharp Wave Biomarkers in the Hypoxic-Ischemic EEG of Preterm Sheep.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We have recently demonstrated that micro-scale Sharp waves in the first few hours EEG of asphyxiated preterm fetal sheep models are the reliable prognostic biomarkers for Hypoxic-Ischemic Encephalopathy (HIE). Higher number of sharp waves within the ...

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

The Journal of antimicrobial chemotherapy
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...

Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery.

Methods in molecular biology (Clifton, N.J.)
CITRUS is a supervised machine learning algorithm designed to analyze single cell data, identify cell populations, and identify changes in the frequencies or functional marker expression patterns of those populations that are significantly associated...