AIMC Topic: Machine Learning

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Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Neuroinformatics
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET),...

An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.

Journal of digital imaging
Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors...

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

Neuroinformatics
Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automa...

Hemodynamic Instability and Cardiovascular Events After Traumatic Brain Injury Predict Outcome After Artifact Removal With Deep Belief Network Analysis.

Journal of neurosurgical anesthesiology
BACKGROUND: Hemodynamic instability and cardiovascular events heavily affect the prognosis of traumatic brain injury. Physiological signals are monitored to detect these events. However, the signals are often riddled with faulty readings, which jeopa...

Statistical Learning Methods to Determine Immune Correlates of Herpes Zoster in Vaccine Efficacy Trials.

The Journal of infectious diseases
Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Z...

[Application of machine learning in the CRISPR/Cas9 system].

Yi chuan = Hereditas
The third generation of the CRISPR/Cas9-mediated genome fixed-point editing technology has been widely used in the field of gene editing and gene expression regulation. How to improve the on-target efficiency and specificity of this system, as well a...

[Applications of machine learning in clinical decision support in the omic era].

Yi chuan = Hereditas
With the development of the omic technologies, the acquisition approaches of various biological data on different levels and types are becoming more mature. As a large amount of data will be produced in the process of diagnosis and treatment of disea...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

Nucleic acids research
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved assessment of coding potential, a cornerstone of genome annotation, and for machine-driven discovery of biological knowledge. While traditional, featu...