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Found 26 papers, 3 papers with code
Automated Measurement of Vascular Calcification in Femoral Endarterectomy Patients Using Deep Learning
However, manual analysis of CTA images is time-consuming and tedious.
TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning
Pathological alterations in the human vascular system underlie many chronic diseases, such as atherosclerosis and aneurysms.
Wordification: A New Way of Teaching English Spelling Patterns
It is estimated that 85% of people in juvenile delinquent systems cannot adequately read or write, that more than half of those with substance abuse issues have complications in reading or writing and that two-thirds of those who do not complete high school lack proper literacy skills.
nD-PDPA: nDimensional Probability Density Profile Analysis
Despite the recent advances in various Structural Genomics Projects, a large gap remains between the number of sequenced and structurally characterized proteins.
Comprehensive and user-analytics-friendly cancer patient database for physicians and researchers
Nuanced cancer patient care is needed, as the development and clinical course of cancer is multifactorial with influences from the general health status of the patient, germline and neoplastic mutations, co-morbidities, and environment.
Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks
The use of sensors available through smart devices has pervaded everyday life in several applications including human activity monitoring, healthcare, and social networks.
Application of Dimensional Reduction in Artificial Neural Networks to Improve Emergency Department Triage During Chemical Mass Casualty Incidents
Chemical Mass Casualty Incidents (MCI) place a heavy burden on hospital staff and resources.
Application of Machine Learning to Sleep Stage Classification
Here we have shown the potential of various machine learning classifiers to automatically, accurately, and reliably classify vigilance states based on a single EEG reading and a single EMG reading.
Application of Machine Learning in Early Recommendation of Cardiac Resynchronization Therapy
We have demonstrated that using machine learning approaches can identify HF patients with a high probability of a positive CRT response (95% accuracy), and of equal importance, identify those HF patients that would not derive a functional benefit from CRT.
MedSensor: Medication Adherence Monitoring Using Neural Networks on Smartwatch Accelerometer Sensor Data
Poor medication adherence presents serious economic and health problems including compromised treatment effectiveness, medical complications, and loss of billions of dollars in wasted medicine or procedures.
Reduction in the complexity of 1D 1H-NMR spectra by the use of Frequency to Information Transformation
Analysis of 1H-NMR spectra is often hindered by large variations that occur during the collection of these spectra.
TALI: Protein Structure Alignment Using Backbone Torsion Angles
This article introduces a novel protein structure alignment method (named TALI) based on the protein backbone torsion angle instead of the more traditional distance matrix.
An Investigation in Optimal Encoding of Protein Primary Sequence for Structure Prediction by Artificial Neural Networks
Our investigations concluded that one-hot encoding, the use of LSTMs, and window sizes of 9, 11, and 15 produce the optimal outcome.
A Comparative study of Artificial Neural Networks Using Reinforcement learning and Multidimensional Bayesian Classification Using Parzen Density Estimation for Identification of GC-EIMS Spectra of Partially Methylated Alditol Acetates
The developed system is implemented on the world wide web, and is intended to identify PMAAs using submitted spectra of these molecules recorded on any GC-EIMS instrument.
Parallel, Self Organizing, Consensus Neural Networks
The architecture has all the advantages of the previous models such as self-organization and possesses some other superior characteristics such as input parallelism and decision making based on consensus.
Identification of 1H-NMR Spectra of Xyloglucan Oligosaccharides: A Comparative Study of Artificial Neural Networks and Bayesian Classification Using Nonparametric Density Estimation
Proton nuclear magnetic resonance (1H-NMR) is a widely used tool for chemical structural analysis.
A Preliminary Investigation in the Molecular Basis of Host Shutoff Mechanism in SARS-CoV
Recent events leading to the worldwide pandemic of COVID-19 have demonstrated the effective use of genomic sequencing technologies to establish the genetic sequence of this virus.
Recognition of Smoking Gesture Using Smart Watch Technology
Diseases resulting from prolonged smoking are the most common preventable causes of death in the world today.
De Novo Assembly of Uca minax Transcriptome from Next Generation Sequencing
High-throughput cDNA sequencing (RNA-seq) is a very powerful technique to quantify gene expression in an unbiased way.
State Transition Modeling of the Smoking Behavior using LSTM Recurrent Neural Networks
The use of sensors has pervaded everyday life in several applications including human activity monitoring, healthcare, and social networks.
Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques
We report an object tracking algorithm that combines geometrical constraints, thresholding, and motion detection for tracking of the descending aorta and the network of major arteries that branch from the aorta including the iliac and femoral arteries.
An AI model for Rapid and Accurate Identification of Chemical Agents in Mass Casualty Incidents
In this report we examine the effectiveness of WISER in identification of a chemical culprit during a chemical based Mass Casualty Incident (MCI).
Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks
While Hydroxyurea reduces the complications associated with Sickle Cell Anemia in some patients, others do not benefit from this drug and experience deleterious effects since it is also a chemotherapeutic agent.
Improvements of the REDCRAFT Software Package
Traditional approaches to elucidation of protein structures by NMR spectroscopy rely on distance restraints also known as nuclear Overhauser effects (NOEs).
Using Residual Dipolar Couplings from Two Alignment Media to Detect Structural Homology
The method of Probability Density Profile Analysis has been introduced previously as a tool to find the best match between a set of experimentally generated Residual Dipolar Couplings and a set of known protein structures.
Protein Fold Family Recognition From Unassigned Residual Dipolar Coupling Data
Despite many advances in computational modeling of protein structures, these methods have not been widely utilized by experimental structural biologists.
