AIMC Topic: Linear Models
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Artificial Intelligence Models Predict Operative Versus Nonoperative Management of Patients with Adult Spinal Deformity with 86% Accuracy.
World neurosurgery
May 17, 2020
OBJECTIVE: Patients with ASD show complex and highly variable disease. The decision to manage patients operatively is largely subjective and varies based on surgeon training and experience. We sought to develop models capable of accurately discrimina...
The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields.
Scientific reports
May 12, 2020
The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consisted of 82,433 VFs from 16,836 eyes. Testing dataset 1 consisted of test-retest VFs from 104 eyes wit...
Comparison of statistical and machine learning models for healthcare cost data: a simulation study motivated by Oncology Care Model (OCM) data.
BMC health services research
Apr 25, 2020
BACKGROUND: The Oncology Care Model (OCM) was developed as a payment model to encourage participating practices to provide better-quality care for cancer patients at a lower cost. The risk-adjustment model used in OCM is a Gamma generalized linear mo...
End-to-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism.
Sensors (Basel, Switzerland)
Apr 20, 2020
Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients. Continuous BP monitoring is important for patients with hypertension. Various studies have proposed cuff-less BP monitoring methods using pulse trans...
Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration.
Genomics
Mar 29, 2020
Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understan...
Stable gene selection by self-representation method in fuzzy sample classification.
Medical & biological engineering & computing
Mar 24, 2020
In recent years, microarray technology and gene expression profiles have been widely used to detect, predict, or classify the samples of various diseases. The presence of large genes in these profiles and the small number of samples are known challen...
Predicting Wait Times in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Patient perceptions of wait time during outpatient office visits can affect patient satisfaction. Providing accurate information about wait times could improve patients' satisfaction by reducing uncertainty. However, these are rarely known about effi...
Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments.
BioMed research international
Feb 25, 2020
BACKGROUND: Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the reliability of variant calls. Alt...
Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.
Clinical nutrition (Edinburgh, Scotland)
Feb 14, 2020
BACKGROUND: There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner avail...
Coding with transient trajectories in recurrent neural networks.
PLoS computational biology
Feb 13, 2020
Following a stimulus, the neural response typically strongly varies in time and across neurons before settling to a steady-state. While classical population coding theory disregards the temporal dimension, recent works have argued that trajectories o...
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