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Analysis of institutional authors

Platero, CCorresponding AuthorTobar, McAuthor

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November 30, 2020
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Predicting Alzheimer's conversion in mild cognitive impairment patients using longitudinal neuroimaging and clinical markers

Publicated to: Brain Imaging and Behavior. 15 (4): 1728-1738 - 2021-08-01 15(4), DOI: 10.1007/s11682-020-00366-8

Authors:

Platero, Carlos; Tobar, M Carmen
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Affiliations

Univ Politecn Madrid, Hlth Sci Technol Grp, Ronda Valencia 3, Madrid 28012, Spain - Author

Abstract

Patients with mild cognitive impairment (MCI) have a high risk for conversion to Alzheimer's disease (AD). Early diagnose of AD in MCI subjects could help to slow or halt the disease progression. Selecting a set of relevant markers from multimodal data to predict conversion from MCI to probable AD has become a challenging task. The aim of this paper is to quantify the impact of longitudinal predictive models with single- or multisource data for predicting MCI-to-AD conversion and identifying a very small subset of features that are highly predictive of conversion. We developed predictive models of MCI-to-AD progression that combine magnetic resonance imaging (MRI)-based markers (cortical thickness and volume of subcortical structures) with neuropsychological tests. These models were built with longitudinal data and validated using baseline values. By using a linear mixed effects approach, we modeled the longitudinal trajectories of the markers. A set of longitudinal features potentially discriminating between MCI subjects who convert to dementia and those who remain stable over a period of 3 years was obtained. Classifier were trained using the marginal longitudinal trajectory residues from the selected features. Our best models predicted conversion with 77% accuracy at baseline (AUC = 0.855, 84% sensitivity, 70% specificity). As more visits were available, longitudinal predictive models improved their predictions with 84% accuracy (AUC = 0.912, 83% sensitivity, 84% specificity). The proposed approach was developed, trained and evaluated using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with a total of 2491 visits from 610 subjects.
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Keywords

Alzheimer diseaseAlzheimer&#8217Alzheimer’s diseaseAlzheimer’s diseaseBiomarkersBrain atrophyClassificationCognitive dysfunctionCohortCortical thicknessDiagnosisDiseaseDisease progressionHumansLongitudinal analysisMagnetic resonance imagingMciMriNeuroimagingPatternsS diseaseSegmentation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Brain Imaging and Behavior due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2021, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Radiology, Nuclear Medicine and Imaging.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 2.02. This indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: ESI Nov 13, 2025)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 2.2 (source consulted: FECYT Mar 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2026-04-24, the following number of citations:

  • WoS: 27
  • Scopus: 28
  • Europe PMC: 24
  • Open Alex: 35
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-24:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 30.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 30 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 10.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).
  • The number of mentions in news outlets: 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/91864/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 70
  • Downloads: 32
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (PLATERO DUEÑAS, CARLOS) .

the author responsible for correspondence tasks has been PLATERO DUEÑAS, CARLOS.

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