A Deep Learning Framework for Deriving Non-Invasive Intracranial Pressure Waveforms from Transcranial Doppler.
Sign Up to like & getrecommendations! Published in 2023 at "Annals of neurology"
DOI: 10.1002/ana.26682
Abstract: Increased intracranial pressure (ICP) causes disability and mortality in the neuro-intensive care population. Current methods for monitoring ICP are invasive. We designed a deep learning framework using a domain adversarial neural network to estimate noninvasive… read more here.
Keywords: non invasive; framework; pressure; deep learning ... See more keywords
Optical fog‐assisted smart learning framework to enhance students’ employability in engineering education
Sign Up to like & getrecommendations! Published in 2019 at "Computer Applications in Engineering Education"
DOI: 10.1002/cae.22120
Abstract: In the present scenario, the state of engineering education worldwide is facing a big challenge of the employability of graduates. Cloud computing technology has changed the educational landscape by allowing educators and administrators to shift… read more here.
Keywords: framework; learning framework; employability; engineering education ... See more keywords
Robust privacy‐preserving federated learning framework for IoT devices
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22993
Abstract: Federated Learning (FL) is a framework where multiple parties can train a model jointly without sharing private data. Private information protection is a critical problem in FL. However, the communication overheads of existing solutions are… read more here.
Keywords: federated learning; iot devices; framework; privacy preserving ... See more keywords
Glioma grading using a machine‐learning framework based on optimized features obtained from T1 perfusion MRI and volumes of tumor components
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Magnetic Resonance Imaging"
DOI: 10.1002/jmri.26704
Abstract: Glioma grading between intermediate grades (Grade II vs. III and Grade III vs. IV) as well as multiclass grades (Grade II vs. III vs. IV) is challenging and needs to be addressed. read more here.
Keywords: machine learning; using machine; grading using; glioma grading ... See more keywords
DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions
Sign Up to like & getrecommendations! Published in 2019 at "PROTEOMICS"
DOI: 10.1002/pmic.201900019
Abstract: Annotation of protein functions plays an important role in understanding life at the molecular level. High‐throughput sequencing produces massive numbers of raw proteins sequences and only about 1% of them have been manually annotated with… read more here.
Keywords: protein; deep learning; learning framework; functions protein ... See more keywords
A Bayesian Sequential Learning Framework to Parameterise Continuum Models of Melanoma Invasion into Human Skin
Sign Up to like & getrecommendations! Published in 2019 at "Bulletin of Mathematical Biology"
DOI: 10.1007/s11538-018-0532-1
Abstract: We present a novel framework to parameterise a mathematical model of cell invasion that describes how a population of melanoma cells invades into human skin tissue. Using simple experimental data extracted from complex experimental images,… read more here.
Keywords: bayesian sequential; invasion; sequential learning; biology ... See more keywords
A deep learning framework using CNN and stacked Bi-GRU for COVID-19 predictions in India
Sign Up to like & getrecommendations! Published in 2021 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-021-01988-1
Abstract: The novel coronavirus infection (COVID-19) first appeared in Wuhan, China, in December 2019. COVID-19 declared as a global pandemic by the WHO was the most rapidly spreading disease all across the world. India, the second… read more here.
Keywords: cnn stacked; framework; using cnn; deep learning ... See more keywords
A learning framework for information block search based on probabilistic graphical models and Fisher Kernel
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-017-0657-9
Abstract: Contrary to traditional Web information retrieval methods that can only return a ranked list of Web pages and only allow search terms in the query, we have developed a novel learning framework for retrieving precise… read more here.
Keywords: information; block; search; information block ... See more keywords
Deep learning framework for carbon nanotubes: Mechanical properties and modeling strategies
Sign Up to like & getrecommendations! Published in 2021 at "Carbon"
DOI: 10.1016/j.carbon.2021.08.091
Abstract: Tensile tests at room temperature are performed using molecular dynamics on all configurations of single-walled carbon nanotubes up to 4 nm in diameter. Distributions of the Young’s modulus, Poisson’s ratio, ultimate tensile strength and fracture… read more here.
Keywords: modeling strategies; carbon nanotubes; deep learning; mechanical properties ... See more keywords
MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease.
Sign Up to like & getrecommendations! Published in 2019 at "Cell systems"
DOI: 10.1016/j.cels.2019.04.003
Abstract: Most gene expression datasets generated by individual researchers are too small to fully benefit from unsupervised machine-learning methods. In the case of rare diseases, there may be too few cases available, even when multiple studies are… read more here.
Keywords: transfer learning; rare disease; disease; multiplier transfer ... See more keywords
AUTOMATED MACHINE LEARNING FRAMEWORK TO PROCESS ELECTRONIC MEDICAL RECORDS FOR CARDIOVASCULAR COMPLICATION RISK ASSESSMENT
Sign Up to like & getrecommendations! Published in 2022 at "Journal of the American College of Cardiology"
DOI: 10.1016/s0735-1097(22)03008-x
Abstract: Background: The abundance of data in electronic medical records presents countless opportunities for machine learning (ML) analyses;however, manual interpretation of the relationship between features, model selection, and parameter optimization can be challenging. In our work,… read more here.
Keywords: learning framework; electronic medical; machine; risk ... See more keywords