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2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

2020 IEEE journal of biomedical and health informatics  
., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre, C., JBHI Jan  ...  Tabik, S., +, Construction of Empirical Care Pathways Process Models From Multiple Real-World Datasets.  ...  ., +, JBHI Sept. 2020 2621-2629 Characterizing Alzheimer's Disease With Image and Genetic Biomarkers Using Supervised Topic Models.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

Automated mitosis detection in histopathology based on non-gaussian modeling of complex wavelet coefficients

Tao Wan, Wanshu Zhang, Min Zhu, Jianhui Chen, Alin Achim, Zengchang Qin
2017 Neurocomputing  
This study aims at improving the accuracy of automated mitosis detection by characterizing mitotic cells in wavelet based multi-resolution representations via a non-Gaussian modeling method.  ...  models, leading to more accurate detection results.  ...  Acknowledgments This work was partially supported by the National Natural Science Foundation of China under award Nos. 61305047 and 61401012.  ... 
doi:10.1016/j.neucom.2017.01.008 fatcat:be3zcs3d4zftvdjd2tvkl4l3d4

A Review of Automated Speech and Language Features for Assessment of Cognition and Thought Disorders

Rohit Nihar Uttam Voleti, Julie Liss, Visar Berisha
2019 IEEE Journal on Selected Topics in Signal Processing  
This work relies on extracting a set of features from recorded and transcribed speech for objective assessments of speech and language, early diagnosis of neurological disease, and tracking of disease  ...  We conclude the review with a proposal of new research directions to further advance the field.  ...  As an example, Roark et al. considered a variety of speech and language features to detect mild cognitive impairment (MCI), often a precursor to Alzheimer's disease (AD) [4] .  ... 
doi:10.1109/jstsp.2019.2952087 pmid:33907590 pmcid:PMC8074691 fatcat:a6t24cpp6jbdxbxq5wzd3uz6jq

Artificial Intelligence, speech and language processing approaches to monitoring Alzheimer's Disease: a systematic review [article]

Sofia de la Fuente Garcia, Craig Ritchie, Saturnino Luz
2020 arXiv   pre-print
This paper summarises current findings on the use of artificial intelligence, speech and language processing to predict cognitive decline in the context of Alzheimer's Disease, detailing current research  ...  Language is a valuable source of clinical information in Alzheimer's Disease, as it declines concurrently with neurodegeneration.  ...  Conflict of Interest/Disclosure Statement The authors have no conflict of interest to report. 24 de la Fuente Garcia, Ritchie & Luz / AI approaches to monitoring AD  ... 
arXiv:2010.06047v1 fatcat:gowcdpj6pfddfns3gh7amtqpze

A Tour of Unsupervised Deep Learning for Medical Image Analysis [article]

Khalid Raza, Nripendra Kumar Singh
2018 arXiv   pre-print
Interpretation of medical images for diagnosis and treatment of complex disease from high-dimensional and heterogeneous data remains a key challenge in transforming healthcare.  ...  This review systematically presents various unsupervised models applied to medical image analysis, including autoencoders and its several variants, Restricted Boltzmann machines, Deep belief networks,  ...  Conflict of Interest Statement Authors declare that there is no any conflict of interest in the publication of this manuscript.  ... 
arXiv:1812.07715v1 fatcat:4dd75wfhvnf7db3v72575tikoi

2020 Index IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 17

2021 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
P Pain Classification of Patients with Coronary Microvascular Dysfunction.  ...  -Dec. 2020 2005-2016 Gene Expressions, Hippocampal Volume Loss, and MMSE Scores in Computation of Progression and Pharmacologic Therapy Effects for Alzheimer's Disease.  ...  Associations Based on Similarities and Bi-Random Walk on Disease and Microbe Networks; TCBB Sept.  ... 
doi:10.1109/tcbb.2020.3047571 fatcat:x3kmrpexsve6bnjtd3dh6ntkyy

Benchmarking functional connectome-based predictive models for resting-state fMRI

Kamalaker Dadi, Mehdi Rahim, Alexandre Abraham, Darya Chyzhyk, Michael Milham, Bertrand Thirion, Gaël Varoquaux
2019 NeuroImage  
Here, we consider a specific type of studies, using predictive models on the edge weights of functional connectomes, for which we highlight the best modeling choices.  ...  We systematically study the prediction performances of models in 6 different cohorts and a total of 2000 individuals, encompassing neuro-degenerative (Alzheimer's, Post-traumatic stress disorder), neuro-psychiatric  ...  Detection of brain functional-connectivity difference in post-stroke patients using group-level covariance modeling, in: MICCAI. Varoquaux, G., Craddock, R.C., 2013.  ... 
doi:10.1016/j.neuroimage.2019.02.062 pmid:30836146 fatcat:gyc6jxopp5gihn3alwgrf7zcge

Progress in neural networks for EEG signal recognition in 2021

Ildar Rakhmatulin
2021 Zenodo  
But many different models of neural networks complicate the process of understanding the real situation in this area.  ...  We also examined in detail the process of extracting features from EEG signals using neural networks.  ...  [38] used neural networks for recognizing diseases such as alcoholism, Bi et al. [39] for recognizing early Alzheimer's disease, Shim et al.  ... 
doi:10.5281/zenodo.4646406 fatcat:qwtrz72ymfgihlxa2u5qtikbje

A Survey on Classification algorithms of Brain Images in Alzheimer's disease based on Feature Extraction techniques

Ruhul Amin Hazarika, Arnab Kumar Maji, Samarendra Nath Sur, Babu Sena Paul, Debdatta Kandar
2021 IEEE Access  
For automated detection of Alzheimer's disease, a novel AD classification approach is proposed in the literature [117] .  ...  The Local Entropy Minimization with a bi-cubic Spline (LEMS) model is used for noise removal and intensity homogeneity correction.  ... 
doi:10.1109/access.2021.3072559 fatcat:cc4ffd325naozaxs63geaut76i

Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations

Jaouher Ben Ali, Lotfi Saidi, Aymen Mouelhi, Brigitte Chebel-Morello, Farhat Fnaiech
2015 Engineering applications of artificial intelligence  
In this work, an effort is made to characterize seven bearing states depending on the energy entropy of Intrinsic Mode Functions (IMFs) resulted from the Empirical Modes Decomposition (EMD).  ...  Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are used for feature reduction.  ...  Acknowledgment Authors wish to thank the Center for Intelligent Maintenance Systems (IMS), University of Cincinnati, USA, for his permission to use his bearing data.  ... 
doi:10.1016/j.engappai.2015.03.013 fatcat:ugs7kqixvfamjfjvfjkivqwv24

Pattern identification of biomedical images with time series: Contrasting THz pulse imaging with DCE-MRIs

Xiao-Xia Yin, Sillas Hadjiloucas, Yanchun Zhang, Min-Ying Su, Yuan Miao, Derek Abbott
2016 Artificial Intelligence in Medicine  
of inferring disease proliferation.  ...  Feature extraction and classification methods based on feature vectors using the above processing techniques are reviewed.  ...  The work aims to highlight progress towards a generic framework for the automated quantitative assessment of disease proliferation using both sensing modalities.  ... 
doi:10.1016/j.artmed.2016.01.005 pmid:26951630 fatcat:usz7o4ejqbhbxntbu34zhg32iu

Implementation and Use of Disease Diagnosis Systems for Electronic Medical Records Based on Machine Learning: A Complete Review

Jahanzaib Latif, Chuangbai Xiao, Shanshan Tu, Sadaqat Ur Rehman, Azhar Imran, Anas Bilal
2020 IEEE Access  
Various techniques have been proposed for automatic extraction of useful information, and accurate diagnosis of diseases.  ...  The objective of this survey paper is to highlight both the strong and weak points of various proposed techniques in the disease diagnosis.  ...  Bi-directional 2017 992 Chinese EMRs Multiple diseases Precision: Transfer Bi-directional [106] LSTM RNN (500 discharge 91.23%, Recall: LSTM RNN for Named summaries and 492 92.45%, F- Entity Recognition  ... 
doi:10.1109/access.2020.3016782 fatcat:j76bwlyrj5dv5mhhsvs4apynje

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Errors in Alzheimer's Disease with an Unsupervised Learning-based Approach Gabriel Lima, Rodrigo Monteiro, Paulo Rocha, Anthony Lins and Carmelo Bastos-Filho .......... 2905 Optimization of Fund Periodic  ...  on Simple and Difficult Many-Objective Test Problems Longcan Chen, Ke Shang and Hisao Ishibuchi .......... 2461 Automated Detection of Microaggression using Machine Learning Omar Ali, Nancy Scheidt, Alexander  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Data Analysis Methods for Software Systems

Jolita Bernatavičienė
2021 Vilnius University Proceedings  
The idea of such workshop came up at the Institute of Mathematics and Informatics that now is the Institute of Data Science and Digital Technologies of Vilnius University.  ...  Of course, the number of participants coming from abroad is much lower, as there are still doubts about the safety of long-distance travel.  ...  , not excluding hard to detect symptoms of Alzheimer's and related diseases.  ... 
doi:10.15388/damss.12.2021 fatcat:iefv6bz3drcrfpcwxoaqmu3gra

Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

Farshid Sepehrband, Ryan P. Cabeen, Jeiran Choupan, Giuseppe Barisano, Meng Law, Arthur W. Toga
2019 NeuroImage  
Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases.  ...  Diffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders.  ...  progression of mild cognitive impairment (MCI) and early Alzheimer's disease (AD).  ... 
doi:10.1016/j.neuroimage.2019.04.070 pmid:31051291 pmcid:PMC6591070 fatcat:c324yspcnzdqnf365jwuztegei
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