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An Overview of Various Computing Methods in Psychiatry and Neuropsychiatry
2017
International Journal for Research in Applied Science and Engineering Technology
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This review paper presents an overview of various computing methods for diagnosis of neuropsychiatric diseases. ...
Related work is concerned with various computing methods and their involvement in medical diagnosis. ...
The result of this system is certainty factor with range between -1 to 1. In this paper, author [17] implemented rule-based expert system for Alzheimer's disease diagnosis. ...
doi:10.22214/ijraset.2017.9183
fatcat:jxqjzm4kfndvrjm4srldqlbv3e
A Bayesian network decision model for supporting the diagnosis of dementia, Alzheimer׳s disease and mild cognitive impairment
2014
Computers in Biology and Medicine
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Neurodegenerative diseases, such as Alzheimer's Disease (AD), have high prevalence in the elderly population. ...
The network structure was built based on current diagnostic criteria and input from physicians who are experts in this domain. ...
Acknowledgments We thank the Center of the Consortium to Establish a Registry for Alzheimer's Disease for kindly providing the patients' cases set used in this study. ...
doi:10.1016/j.compbiomed.2014.04.010
pmid:24946259
fatcat:ozm3w3kvc5a5bo4vkzmf3dzi6q
A Study on the Expert System of Internal Medicine Diagnosis
2015
MATEC Web of Conferences
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diagnosis from the angle of computer based on a brief introduction of the internal medicine diagnosis principle. ...
As for diseases of respiratory system, pharyngitis, cough and fever are characteristics for diagnosis. ...
doi:10.1051/matecconf/20152205006
fatcat:d5wfljzfprbgpmxodbw5pf2u7m
Improved Application of Paraconsistent Artificial Neural Networks in Diagnosis of Alzheimer's Disease
2011
Neuroscience International
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for recognizing predetermined patterns of EEG activity and to assess its value as a possible complementary method for AD diagnosis. ...
Problem statement: The visual analysis of Electroencephalogram (EEG) activity has shown useful as a complementary tool in Alzheimer Disease (AD diagnosis) when the diagnosis remains uncertain, in addition ...
Data analysis-expert system for high frequency band concentration: This expert system is utilized for Alpha band concentration in the exam. ...
doi:10.3844/amjnsp.2011.54.64
fatcat:3t6mexb5uzh4ph5ummwgb2d2fy
Improved Application of Paraconsistent Artificial Neural Networks in Diagnosis of Alzheimer's Disease
2011
Neuroscience International
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for recognizing predetermined patterns of EEG activity and to assess its value as a possible complementary method for AD diagnosis. ...
Problem statement: The visual analysis of Electroencephalogram (EEG) activity has shown useful as a complementary tool in Alzheimer Disease (AD diagnosis) when the diagnosis remains uncertain, in addition ...
Data analysis-expert system for high frequency band concentration: This expert system is utilized for Alpha band concentration in the exam. ...
doi:10.3844/amjnsp.2011.17.27
fatcat:ikqilkxohbabvm5vhu5huulnbe
Multimodal prediction of conversion to Alzheimer's disease based on incomplete biomarkers∗This work was supported by the Bernstein Computational Program of the German Federal Ministry of Education and Research (01GQ1001C, 01GQ0851, GRK 1589/1), the European Regional Development Fund of the European Union (10153458 and 10153460), and Philips Research.∗
2015
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
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Methods: Based on Alzheimer's Disease Neuroimaging Initiative data from MCI-patients including all available modalities, we predicted the conversion to AD within 3 years. ...
This study investigates the prediction of mild cognitive impairment-to-Alzheimer's disease (MCI-to-AD) conversion based on extensive multimodal data with varying degrees of missing values. ...
Acknowledgments The authors would like to thank Catharina Lange, Anja Maeurer, Anna Roberts, Lothar Spies, and Per Suppa for their advice regarding the expert features, Fabian Wenzel and Daniel Gieschen ...
doi:10.1016/j.dadm.2015.01.006
pmid:27239505
pmcid:PMC4877756
fatcat:jb4rayhnjbczrlvg4qsklxnham
Explainable Artificial Intelligence (XAI) in Biomedicine: Making AI Decisions Trustworthy for Physicians and Patients
2021
BioMedInformatics
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It is pointless to ask for an explanation for a decision. A detailed understanding of the mathematical details of an AI algorithm may be possible for experts in statistics or computer science. ...
When the diagnosis or selection of a therapy is no longer made solely by the physician, but to a significant extent by a machine using algorithms, decisions become nontransparent. ...
physician in the case of AI-based clinical decisions related to diagnosis, treatment, or prognosis of a disease. ...
doi:10.3390/biomedinformatics2010001
fatcat:tcpsshmsevaazjngzd2mxzzexu
Longitudinal Speech Biomarkers for Automated Alzheimer's Detection
2021
Frontiers in Computer Science
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samples and aggregates biomarker features from the sensory stream and cognitive core creating a multi-modal graph neural network of symbolic compositional models for the target task. ...
We introduce a novel audio processing architecture, the Open Voice Brain Model (OVBM), improving detection accuracy for Alzheimer's (AD) longitudinal discrimination from spontaneous speech. ...
There is an extensive cough-based diagnosis research of respiratory diseases but to our knowledge, no one had applied it to discriminate other, apparently unrelated, diseases like Alzheimer's. ...
doi:10.3389/fcomp.2021.624694
fatcat:m3kdwrsmbvgtlcdmjuccctkmrq
Intelligent diagnosis of jaundice with dynamic uncertain causality graph model
2017
Journal of Zhejiang University SCIENCE B
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Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. ...
A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. ...
Discussion This study proposed a computer-aided diagnostic system of jaundice in primary clinics based on the DUCG model. ...
doi:10.1631/jzus.b1600273
pmid:28471111
pmcid:PMC5442976
fatcat:6u4cg6h4gbcstpft7x7obneb6a
Development and validation of an interpretable deep learning framework for Alzheimer's disease classification
2020
Brain
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This framework provides a clinically adaptable strategy for using routinely available imaging techniques such as MRI to generate nuanced neuroimaging signatures for Alzheimer's disease diagnosis, as well ...
of individual Alzheimer's disease risk en route to accurate diagnosis. ...
(17SDG33670323) from the American Heart Association, and a Hariri Research Award from the Hariri Institute for Computing and Computational Science & Engineering at Boston University, Framingham Heart ...
doi:10.1093/brain/awaa137
pmid:32357201
fatcat:gy62vvhwevccflc57zfjqbj7fy
Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system
2004
BMC Genomics
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Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. ...
We define a new term "patholog" to mean a homolog of a human disease-related gene encoding a product (transcript, anti-sense or protein) potentially relevant to disease. ...
Acknowledgements DS is the recipient of a scholarship from the Canberra Hospital Salaried Specialists Private Practice Fund. ...
doi:10.1186/1471-2164-5-28
pmid:15115540
pmcid:PMC420239
fatcat:5up4kmbwujdefeyh7hxmpcxgay
Implementation and Use of Disease Diagnosis Systems for Electronic Medical Records Based on Machine Learning: A Complete Review
2020
IEEE Access
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Medical expert systems are generally concerned on the computer writing programs to perform disease diagnosis. ...
Initially, some medical expert systems are designed for automatic diagnosis of diseases. ...
doi:10.1109/access.2020.3016782
fatcat:j76bwlyrj5dv5mhhsvs4apynje
Symbolic Entropy Analysis and Its Applications
2018
Entropy
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This editorial explains the scope of the special issue and provides a thematic introduction to the contributed papers. ...
Accordingly, the authors noticed that in most brain regions had lower dLZC values for patients suffering from Alzheimer's disease than for age-matched control subjects, suggesting a more limited richness ...
attributes and, finally, an expert classifier tailored for each high-confidence label. ...
doi:10.3390/e20080568
pmid:33265656
fatcat:rhkxu3gktjbfvhs576wfdjfbhi
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
[article]
2021
arXiv
pre-print
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Artificial Intelligence has emerged as a useful aid in numerous clinical applications for diagnosis and treatment decisions. ...
for medical image analysis applications based on the type of generated explanations and technical similarities. ...
[137] utilized occlusion maps for interpretability of a model developed for the diagnosis of Alzheimer's disease. ...
arXiv:2111.02398v1
fatcat:glrfdkbcqrbqto2nrl7dnlg3gq
Chronicles of Alzheimer's Disease: A Medicinal & Therapeutic Overview in Bangladeshi Aspect
2019
Journal of Pharmaceutical Research International
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Nervous system and Neurological disorder sounds like a deep-sea of neurobiological harmony, reflecting a glorious bond and symbolizing a deep sign of interrelated linkages. ...
A handful number of patients been analysed through the regular observations based on their previous therapeutic history, expert opinions of scientists and physicians, as well as a smartly organized collection ...
: Neuroscience; nervous system; Alzheimer's disease; neurodegenerative disease; medication. ...
doi:10.9734/jpri/2019/v30i530282
fatcat:vdevvyfz5rdhvpqeydz5easjyy
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