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Predicting Clinical Variable from MRI Features: Application to MMSE in MCI [chapter]

S. Duchesne, A. Caroli, C. Geroldi, G. B. Frisoni, D. Louis Collins
<span title="">2005</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
The ability to predict a clinical variable from automated analysis of single, cross-sectional T1-weighted (T1w) MR scans stands to improve the management of patients with neurological diseases.  ...  We use multiple regression to build linear models from eigenvectors where the projection eigencoordinates of patient data in the reference space are highly correlated with the clinical variable of interest  ...  Mazziotta and Evans (ICBM) for permission to use data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11566465_49">doi:10.1007/11566465_49</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ety5dn5ygbc7vduazpvmfmaeci">fatcat:ety5dn5ygbc7vduazpvmfmaeci</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190505115236/https://link.springer.com/content/pdf/10.1007%2F11566465_49.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b7/a6/b7a62b42f6f514e76ff433f46d43e0e1295d01eb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11566465_49"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A novel relational regularization feature selection method for joint regression and classification in AD diagnosis

Xiaofeng Zhu, Heung-Il Suk, Li Wang, Seong-Whan Lee, Dinggang Shen
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kpkfymbkufcnzjfc5ydyokby4y" style="color: black;">Medical Image Analysis</a> </i> &nbsp;
With the reduced data, we train two support vector regression models to predict the clinical scores of ADAS-Cog and MMSE, respectively, and also a support vector classification model to determine the clinical  ...  Our experimental results showed the efficacy of the proposed method in enhancing the performances of both clinical score prediction and disease status identification, compared to the state-of-the-art methods  ...  Acknowledgments This work was supported in part by NIH grants (EB006733, EB008374  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.media.2015.10.008">doi:10.1016/j.media.2015.10.008</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26674971">pmid:26674971</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4862945/">pmcid:PMC4862945</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xdqesmpifvbuhmsquumrdbouki">fatcat:xdqesmpifvbuhmsquumrdbouki</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191021114217/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4862945&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ed/04/ed049dec09cd412a35bea147c87353d4aa18f2ce.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.media.2015.10.008"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4862945" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Canonical feature selection for joint regression and multi-class identification in Alzheimer's disease diagnosis

Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
<span title="2015-08-09">2015</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qstb4tjynngrpi2vqxycbsil3i" style="color: black;">Brain Imaging and Behavior</a> </i> &nbsp;
In our experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, we use Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) images to jointly predict clinical scores  ...  In this paper, we propose a novel method to transform the original features from different modalities to a common space, where the transformed features become comparable and easy to find their relation  ...  Acknowledgments This work was supported in part by NIH grants (EB006733, EB008374  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11682-015-9430-4">doi:10.1007/s11682-015-9430-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26254746">pmid:26254746</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4747862/">pmcid:PMC4747862</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ce5aejjgpfhahc5gmf7ouvoxne">fatcat:ce5aejjgpfhahc5gmf7ouvoxne</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200430112732/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4747862&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b7/9e/b79eb11189a06bbb31c4ab6e91b949de14c7e829.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11682-015-9430-4"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4747862" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis

Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2014 IEEE Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;
the target response matrix and imposes the information to be preserved in the predicted response matrix.  ...  based on neuroimaging features were highly related to each other.  ...  Note that later in our experiments for clinical score prediction and clinical label classification, we extract one feature from each Region-Of-Interest (ROI) of the brain in MRI or PET, thus this 2,1norm  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2014.395">doi:10.1109/cvpr.2014.395</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26379415">pmid:26379415</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4569014/">pmcid:PMC4569014</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/ZhuSS14.html">dblp:conf/cvpr/ZhuSS14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oo752rev3fg43atx4jx24cqqm4">fatcat:oo752rev3fg43atx4jx24cqqm4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20161118062248/http://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Zhu_Matrix-Similarity_Based_Loss_2014_CVPR_paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/10/05/100511ea26946fb9178e520f76358f3754277583.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2014.395"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4569014" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Federated Morphometry Feature Selection for Hippocampal Morphometry Associated Beta-Amyloid and Tau Pathology

Jianfeng Wu, Qunxi Dong, Jie Zhang, Yi Su, Teresa Wu, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Natasha Lepore, Kewei Chen, Paul M. Thompson, Yalin Wang
<span title="2021-11-25">2021</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wrk3kouosrhcxiprcbguskdipu" style="color: black;">Frontiers in Neuroscience</a> </i> &nbsp;
As potential biomarkers for Aβ/tau pathology, the features from the identified ROIs had greater power for predicting cognitive assessment and for survival analysis than five other imaging biomarkers.  ...  Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects.  ...  With two prediction experiments, we further demonstrate that the morphometric features on our identified ROIs show a stronger predictive power in predicting MMSE scores and future clinical decline in MCI  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnins.2021.762458">doi:10.3389/fnins.2021.762458</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34899166">pmid:34899166</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8655732/">pmcid:PMC8655732</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xywa6ihrwfd5hfl52yx6n2j6d4">fatcat:xywa6ihrwfd5hfl52yx6n2j6d4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220426123453/https://fjfsdata01prod.blob.core.windows.net/articles/files/762458/pubmed-zip/.versions/1/.package-entries/fnins-15-762458/fnins-15-762458.pdf?sv=2018-03-28&amp;sr=b&amp;sig=vf%2B6ukLkgLcXWl1%2FKwGCet%2B4D6wsj9yN8f4GJ%2FXjNNg%3D&amp;se=2022-04-26T12%3A35%3A21Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fnins-15-762458.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1d/e7/1de7d8fc65458433e9edba5b233833302555fc17.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnins.2021.762458"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8655732" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis

Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
<span title="2015-05-21">2015</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h7z73zcffbg2jo4rudbgl6nvfu" style="color: black;">Brain Structure and Function</a> </i> &nbsp;
We further hypothesize that the optimal regression coefficients reflect the relative importance of features in representing the target response variables.  ...  However, to our best knowledge, the existing sparse regression methods mostly try to select features based on the optimal regression coefficients in one step.  ...  [B0101-15-0307, Basic Software Research in Human-level Lifelong Machine Learning (Machine Learning Center)].  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00429-015-1059-y">doi:10.1007/s00429-015-1059-y</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25993900">pmid:25993900</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4714963/">pmcid:PMC4714963</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/p56y3gbo7ndubgti3caagtaenq">fatcat:p56y3gbo7ndubgti3caagtaenq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200208104621/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4714963&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/68/8d/688dd6b21bf185943a868e0823a67dab42b43f77.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00429-015-1059-y"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4714963" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Clinical Features of Mild Cognitive Impairment Differ in the Research and Tertiary Clinic Settings

G.A. Jicha, E. Abner, F.A. Schmitt, G.E. Cooper, N. Stiles, R. Hamon, S. Carr, C.D. Smith, W.R. Markesbery
<span title="">2008</span> <i title="S. Karger AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ci3cg7hejvf7tfyitvlbtd5n54" style="color: black;">Dementia and Geriatric Cognitive Disorders</a> </i> &nbsp;
The variability in clinical and demographic features of MCI reported in the literature in part reflects a combination of inconsistency in the operational definitions of MCI and the study protocols used  ...  All subjects transitioning from normal cognition to MCI in the period from July 1, 2005, to December 31, 2006 (n = 48) were included in the analysis.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1159/000151635">doi:10.1159/000151635</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/18724049">pmid:18724049</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2667338/">pmcid:PMC2667338</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gptrmgokmrc4tfiety2u7vn57e">fatcat:gptrmgokmrc4tfiety2u7vn57e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190228155736/http://pdfs.semanticscholar.org/a5b9/86c5724cb19a90b1eca74b77065bb55f7699.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a5/b9/a5b986c5724cb19a90b1eca74b77065bb55f7699.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1159/000151635"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2667338" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features

Asha Singanamalli, Haibo Wang, Anant Madabhushi
<span title="2017-08-15">2017</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
However, to move toward this opportunity, the most immediate challenge is to accurately distinguish MCI from both HC and AD.  ...  In addition, CaMCCo outperforms all other multi-class classification methods for MCI prediction (PPV: 0.80 vs. 0.67, 0.63).  ...  (NeuroImage, 2014) 40 T1w MRI, FDG PET, CSF Feature selection method and regression to predict clinical variables in addition to class labels 202 AD/HC (Acc: 95.9%, AUC: 98.8), MCI/HC (Acc: 82.0%  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-017-03925-0">doi:10.1038/s41598-017-03925-0</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28811553">pmid:28811553</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5558022/">pmcid:PMC5558022</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/f4zpwwuwezfojgje6tljzloye4">fatcat:f4zpwwuwezfojgje6tljzloye4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200318201651/https://digitalcommons.wustl.edu/cgi/viewcontent.cgi?referer=&amp;httpsredir=1&amp;article=7136&amp;context=open_access_pubs" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/73/12/7312f0733c6c676bc071c6c8ba8e04f1115ce614.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-017-03925-0"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5558022" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments

Yeo Jin Kim, Seong-Kyoung Cho, Hee Jin Kim, Jin San Lee, Juyoun Lee, Young Kyoung Jang, Jacob W. Vogel, Duk L. Na, Changsoo Kim, Sang Won Seo
<span title="2019-01-22">2019</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mvbrssyf7fcebaalpjhndnvzqa" style="color: black;">Alzheimer&#39;s Research &amp; Therapy</a> </i> &nbsp;
Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory.  ...  Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI.  ...  Acknowledgements Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13195-018-0462-z">doi:10.1186/s13195-018-0462-z</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30670089">pmid:30670089</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6343354/">pmcid:PMC6343354</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/etbhuudpvvebjminzz4hndy5fi">fatcat:etbhuudpvvebjminzz4hndy5fi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430120208/https://alzres.biomedcentral.com/track/pdf/10.1186/s13195-018-0462-z" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e4/69/e469a25271d2edc42ad1a938be66428f4f68ff39.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13195-018-0462-z"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343354" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Random Forest Feature Selection, Fusion and Ensemble Strategy: Combining Multiple Morphological MRI Measures to Discriminate among healthy elderly, MCI, cMCI and Alzheimer's disease patients: from the Alzheimer's disease neuroimaging initiative (ADNI) database [article]

Stavros I Dimitriadis, Dimitris Liparas, Magda Tsolaki
<span title="2017-12-18">2017</span> <i title="Cold Spring Harbor Laboratory"> biorxiv/medrxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
New Method: Based on preprocessed MRI images from the organizers of a neuroimaging challenge, we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate  ...  However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from  ...  Acknowledgement We would like to thank the anonymous reviewers for their valuable comments that further improved the quality of the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/236141">doi:10.1101/236141</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/povbko7mevcm5jkoac3ixapfx4">fatcat:povbko7mevcm5jkoac3ixapfx4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190501195412/http://orca.cf.ac.uk/107633/1/Dimitriadis.%20Random%20forest.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/31/10/311067d7a2dba70442548d4f0b0a81ceb5a28afb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/236141"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using MRI and Structural Network Features

Rizhen Wei, Chuhan Li, Noa Fogelson, Ling Li
<span title="2016-04-19">2016</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xyafp6gbr5et3ghi4kqddnyolm" style="color: black;">Frontiers in Aging Neuroscience</a> </i> &nbsp;
In this study, we proposed a classification framework to distinguish MCI converters (MCIc) from MCI non-converters (MCInc) by using a combination of FreeSurfer-derived MRI features and nodal features derived  ...  prediction (18 months), with K-values from 1 to 30.  ...  Thus, early detection of MCI individuals who are suffering from a high risk of conversion from MCI to AD is of increasing clinical importance in potentially delaying or preventing the transition from MCI  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnagi.2016.00076">doi:10.3389/fnagi.2016.00076</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/27148045">pmid:27148045</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4836149/">pmcid:PMC4836149</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ikzulhkrlzbftokpf2z7vfg3pi">fatcat:ikzulhkrlzbftokpf2z7vfg3pi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171008013458/http://publisher-connector.core.ac.uk/resourcesync/data/Frontiers/pdf/f87/aHR0cDovL2pvdXJuYWwuZnJvbnRpZXJzaW4ub3JnL2FydGljbGUvMTAuMzM4OS9mbmFnaS4yMDE2LjAwMDc2L3BkZg%3D%3D.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1d/df/1ddff869b43021e47c89273a9efc1fbf09ccd75c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnagi.2016.00076"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4836149" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

An Efficient Approach for Differentiating Alzheimer's Disease from Normal Elderly Based on Multicenter MRI Using Gray-Level Invariant Features

Muwei Li, Kenichi Oishi, Xiaohai He, Yuanyuan Qin, Fei Gao, Susumu Mori, Satoru Hayasaka
<span title="2014-08-20">2014</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s3gm7274mfe6fcs7e3jterqlri" style="color: black;">PLoS ONE</a> </i> &nbsp;
In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical  ...  The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC) using a support vector machine.  ...  Acknowledgments Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0105563">doi:10.1371/journal.pone.0105563</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25140532">pmid:25140532</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4139346/">pmcid:PMC4139346</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2rg52dwk7faavdtozk6oicks6m">fatcat:2rg52dwk7faavdtozk6oicks6m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171010055840/http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0105563&amp;type=printable" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/81/4f81f0c0019862046710d70b6ea880f989949e9a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pone.0105563"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> plos.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4139346" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis

Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
<span title="2014-07-18">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/sa477uo7lveh7hchpikpixop5u" style="color: black;">NeuroImage</a> </i> &nbsp;
To our best knowledge, the previous methods in the literature mostly used hand-crafted features such as cortical thickness, gray matter densities from MRI, or voxel intensities from PET, and then combined  ...  devise a systematic method for a joint feature representation from the paired patches of MRI and PET with a multimodal DBM.  ...  Acknowledgment This work was supported in part by NIH grants EB006733, EB008374, EB009634, AG041721, MH100217, and AG042599, and also by the National Research Foundation grant (No. 2012-005741) funded  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroimage.2014.06.077">doi:10.1016/j.neuroimage.2014.06.077</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25042445">pmid:25042445</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4165842/">pmcid:PMC4165842</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5cfxrvzalvdhhj3ccztwtkq5uu">fatcat:5cfxrvzalvdhhj3ccztwtkq5uu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200321064122/http://pr.korea.ac.kr/bbs/download.php?bo_table=sub4_1&amp;wr_id=101&amp;no=0" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ac/b3/acb3b02ff9aa058ba78fe6edcbd7da536434672f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroimage.2014.06.077"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165842" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

VentRa. Validation study of the ventricle feature estimation and classification tool to differentiate behavioral variant frontotemporal dementia from psychiatric disorders and other degenerative diseases [article]

Ana L. Manera, Mahsa Dadar, Simon Ducharme, D. Louis Collins
<span title="2022-04-02">2022</span> <i title="Cold Spring Harbor Laboratory"> medRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
from a clinically representative independent dataset.  ...  Results: Using ventricular features to discriminate bvFTD subjects from PPD, VentRa achieved an accuracy of 84%, 71% sensitivity and 89% specificity.  ...  developed automated tool VentRa 6 for the estimation of ventricular features on T1w MRI for the individual prediction of bvFTD within a mixed cohort of subjects from an independent dataset of clinically  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2022.03.29.22273096">doi:10.1101/2022.03.29.22273096</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zqk4i6xadzbnbopf5kxvazzjyu">fatcat:zqk4i6xadzbnbopf5kxvazzjyu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220423191426/https://www.medrxiv.org/content/medrxiv/early/2022/04/02/2022.03.29.22273096.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/07/c8/07c8fd836ca569babde0f978ef2a67f39df4de53.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2022.03.29.22273096"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> medrxiv.org </button> </a>

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

Heung-Il Suk, Seong-Whan Lee, Dinggang Shen
<span title="2013-12-22">2013</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h7z73zcffbg2jo4rudbgl6nvfu" style="color: black;">Brain Structure and Function</a> </i> &nbsp;
Unlike the previous methods that considered simple low-level features such as gray matter tissue volumes from MRI, and mean signal intensities from PET, in this paper, we propose a deep learning-based  ...  Furthermore, thanks to the unsupervised characteristic of the pre-training in deep learning, we can benefit from the target-unrelated samples to initialize parameters of SAE, thus finding optimal parameters  ...  Acknowledgments This work was supported in part by NIH grants EB006733, EB008374, EB009634, AG041721, MH100217, and AG042599, and also by the National Research Foundation grant (No. 2012-005741) funded  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00429-013-0687-3">doi:10.1007/s00429-013-0687-3</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/24363140">pmid:24363140</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4065852/">pmcid:PMC4065852</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ynfewlq3grh5fdhwdjcqbmvg4q">fatcat:ynfewlq3grh5fdhwdjcqbmvg4q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209052432/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4065852&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e9/31/e9319862913357d7c5ec01ce1ad44c95eac8cb74.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00429-013-0687-3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4065852" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
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