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A Survey On Data Mining Techniques To Find Out Type Of Heart Attack
2014
IOSR Journal of Computer Engineering
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Medicinal identification is extremely important but complicated task that should be performed precisely and proficiently. ...
Although substantial advancement has been made in the diagnosis and treatment of heart disease, additional investigation is still needed. ...
They combined maximum clique concept in graph with weighted association rule mining for disease prediction. ...
doi:10.9790/0661-16150105
fatcat:dy66ntdxzrbaxd6t2v3ijh4ew4
Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes
2019
Journal of Biomedical Semantics
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Each concept, represented by an n-gram, is mapped to UMLS using MetaMap; we also developed a bespoke method for mapping short forms (e.g. abbreviations and acronyms). ...
We used a Semantic Deep Learning approach that combines the Semantic Web technologies and Deep Learning to acquire and validate knowledge about 11 well-known medical conditions mined from two sets of unstructured ...
SNOMED CT®, was originally created by The College of American Pathologists. "SNOMED" and "SNOMED CT" are registered trademarks of the IHTSDO. ...
doi:10.1186/s13326-019-0212-6
pmid:31711540
pmcid:PMC6849172
fatcat:vfm3gd524ng3xprcra2z356lha
Research on Classification of Tibetan Medical Syndrome in Chronic Atrophic Gastritis
2019
Applied Sciences
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Classification association rules that integrate association rules with classification are playing an important role in data mining. ...
However, the time cost on constructing the classification model, and predicting new instances, will be long, due to the large number of rules generated during the mining of association rules, which also ...
decision-making support for the diagnosis and treatment of common plateau diseases more scientifically, and achieve the evidence-based intelligence of the diagnosis and treatment by Tibetan medicine. ...
doi:10.3390/app9081664
fatcat:qjpbzrhbhbf5ddbcpzujoccavy
Information Extraction from the Text Data on Traditional Chinese Medicine: A Review on Tasks, Challenges, and Methods from 2010 to 2021
2022
Evidence-Based Complementary and Alternative Medicine
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The practice of traditional Chinese medicine (TCM) began several thousand years ago, and the knowledge of practitioners is recorded in paper and electronic versions of case notes, manuscripts, and books ...
In the future, IE work should be promoted by extracting more existing entities and relations, constructing gold standard data sets, and exploring IE methods based on a small amount of labeled data. ...
of China (Grant no. 61801058) and Talent Fund of Chengdu University of Traditional Chinese Medicine (Grant no. ...
doi:10.1155/2022/1679589
pmid:35600940
pmcid:PMC9122692
fatcat:r7sj7sdoubhwfhcscj227neoiy
Variance analysis and handling of Clinical Pathway: An overview of the state of knowledge
2020
IEEE Access
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INDEX TERMS Clinical pathway, processing methods, text mining, variance. ...
Clinical pathway is a multi-disciplinary treatment plan and work mode, which is favorable for improving healthcare service quality and reducing medical costs. ...
By using data mining technology, process mining technology, data envelopment analysis method, semantic-based and semi-automatic text mining method and other techniques to extract the treatment program, ...
doi:10.1109/access.2020.3020151
fatcat:pe54rtkionfopgz6awtkx7kuzu
Mining the pharmacogenomics literature--a survey of the state of the art
2012
Briefings in Bioinformatics
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text mining tools. ...
This article surveys efforts on text mining of the pharmacogenomics literature, mainly from the period 2008 to 2011. ...
discovery: mining implicit and novel information'). ...
doi:10.1093/bib/bbs018
pmid:22833496
pmcid:PMC3404399
fatcat:por4dnthkrcxjdsir6uc64kdaq
Introduction: selected extended articles from the 2nd International Workshop on Semantics-Powered Data Analytics (SEPDA 2017)
2018
BMC Medical Informatics and Decision Making
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In 2016, President Obama launched the Precision Medicine Initiative (now called "All of Us Research Program") with a $215 million investment to understand how a person's genetics, environment, and lifestyle ...
Big health data has been used in many clinical research applications such as discovering new disease association and personalized treatment with data mining techniques. ...
doi:10.1186/s12911-018-0624-8
pmid:30066636
pmcid:PMC6069756
fatcat:qjkptie33fephlhestivneevg4
Intelligent Health Care: Applications of Deep Learning in Computational Medicine
2021
Frontiers in Genetics
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People need to extract the effective information contained in these big biomedical data to promote the development of precision medicine. ...
With the progress of medical technology, biomedical field ushered in the era of big data, based on which and driven by artificial intelligence technology, computational medicine has emerged. ...
For example, it provides timely treatment for patients by mining the data in the electronic health record to predict the disease, or it analyzes the hidden relationship between diseases and diseases, diseases ...
doi:10.3389/fgene.2021.607471
pmid:33912213
pmcid:PMC8075004
fatcat:f4kaii7egjff3dxiuzyp3puawq
Attribute reduction and missing value imputing with ANN: prediction of learning disabilities
2011
Neural computing & applications (Print)
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This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their ...
A widely accepted formal definition of data mining is given subsequently. Data mining is the nontrivial extraction of implicit previously unknown and potentially useful information about data [4] . ...
Diverse fields such as marketing, customer relationship management, engineering, medicine, crime analysis, expert prediction, web mining, and mobile computing besides others utilize data mining [6] . ...
doi:10.1007/s00521-011-0619-1
fatcat:vss7uf2twvgsxk32gwyy3rxeki
Analysis of Data Mining Techniques and its Applications
2016
International Journal of Computer Applications
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Since the late 90s, efforts have been taken to refine the concept of Knowledge Discovery in Databases and data mining. ...
This paper is aimed at providing a detailed introduction to data mining, review of real world applications pertaining to the concept, big data and data mining techniques, as well as an integrated overview ...
One of the first attempts to precisely explain knowledge discovery was made in [1] , where it was defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information ...
doi:10.5120/ijca2016909249
fatcat:ao4htoqerffmrlvp453pvfclme
Mental Illness from the Perspective of Theoretical Neuroscience
2008
Perspectives in biology and medicine
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Such explanations will also be useful for generating better classifications and treatments of psychiatric disorders.The result should help to eliminate concerns that mental illnesses such as depression ...
to solve the explanation problem of causally connecting neural processes with the behaviors and experiences found in mental illnesses. ...
Like the catch-all category of "fever" in Hippocratic humor-based medicine, the concepts of schizophrenia and depression would be superseded by more precise concepts tied to causal explanations.Then psychiatry ...
doi:10.1353/pbm.0.0030
pmid:18723939
fatcat:whmznpk2tvdtzinndwjyogetxa
PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text
2020
BMC Medical Informatics and Decision Making
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Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. ...
, breast cancer staging and careflow mining. ...
[20] presented an unsupervised framework to normalize the Chinese medical concept by combining disease text with comorbidity. ...
doi:10.1186/s12911-020-01216-9
pmid:32859189
fatcat:ywmonkkuevfi5llwgktwn3cd4a
Thrice Filtered Information Energy Based Particle Swarm Feature Selection (TFIE-PSFS) Method Based Artificial Neural Network Classification for Improving Heart Disease Diagnosis
2019
Asian Journal of Engineering and Applied Technology
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a Medicinal expert. ...
whole, the forecast of heart disease lies upon the conventional method of analysing medical report such as ECG (The Electrocardiogram), MRI (Magnetic Resonance Imaging), Blood Pressure, Stress tests by ...
The researchers in the field of medicine recognize and forecast the disease with the assistance of Data mining techniques [3] .
II. ...
doi:10.51983/ajeat-2019.8.1.1068
fatcat:lit67lo3evhyjm74m6zlc2t4ny
Electronic Medical Records and Machine Learning in Approaches to Drug Development
[chapter]
2020
Artificial Intelligence in Oncology Drug Discovery and Development
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EMRs could help discover phenotypegenotype associations, enhance clinical trial protocols, automate adverse drug event detection and prevention, and accelerate precision medicine research. ...
Although feasible, data mining in EMRs still faces challenges. Existing machine learning tools may help overcome these bottlenecks in EMR mining to unlock new approaches in drug development. ...
Identifying driver genes within the genome and delivering the optimal treatment to such cancer-related targets is known as precision medicine. ...
doi:10.5772/intechopen.92613
fatcat:g7dn33z4d5dc5gisqkyojroc3m
A Survey on Extraction of Causal Relations from Natural Language Text
[article]
2021
arXiv
pre-print
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We initially introduce primary forms existing in the causality extraction: explicit intra-sentential causality, implicit causality, and inter-sentential causality. ...
For example in medicine, the decision to provide a treatment is based on the relationship that the treatment leads to an improvement in patient's condition. ...
[70] utilize verb-pair rules to train NB and SVM to mine implicit causality from Thai texts. ...
arXiv:2101.06426v2
fatcat:hd3ikb7mejcndlq6wsgojv4uoa
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