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Research

28,180 Alzheimer's and dementia studies in plain English, each scored out of 100.

Find studies

Showing 26–50 of 61 studies in Digital health tools published 2018 (page 2 of 3) · 28,180 in the whole library · How the 0–100 score works

Download bibliography of these 61 studies, in this order: BibTeX (.bib) · RIS (.ris)

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

Other subjects

Authors

Names as each record prints them; the same person can appear under two spellings.

Institutions

From OpenAlex; 13,658 studies have no institution on record and are not counted here.

What “Digital health tools” covers

Digital health tools — Apps, wearables, online tests and other technology used to detect, monitor or support people with dementia.

A note on reading research. One study is rarely the final word.

We try to note the size of a study, whether it was in humans or animals, and how early-stage the finding is. If a summary here doesn't make that clear, treat it with extra caution and check the original source.

Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer's disease clinical trials

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer's & dementia (New York, N. Y.) 2018-05-24

Digital technology is transforming the development of drugs for Alzheimer's disease and was the topic of the Alzheimer's Association's Research Roundtable on its May 23-24, 2017 meeting. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Translational research : the journal of laboratory and clinical medicine 2018-01-10

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. 5 key findings →

Design: longitudinal study Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Asymmetry of post-mortem neuropathology in behavioural-variant frontotemporal dementia

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Brain : a journal of neurology 2018-01-01

Antemortem behavioural and anatomic abnormalities have largely been associated with right hemisphere disease in behavioural-variant frontotemporal dementia, but post-mortem neuropathological examination of bilateral hemispheres remains to be defined. 5 key findings →

Participants: 26 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Age- and disease-dependent increase of the mitophagy marker phospho-ubiquitin in normal aging and Lewy body disease

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Autophagy 2018-07-28

Although exact causes of Parkinson disease (PD) remain enigmatic, mitochondrial dysfunction is increasingly appreciated as a key determinant of dopaminergic neuron susceptibility in both familial and sporadic PD. 3 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

MRI Characterizes the Progressive Course of AD and Predicts Conversion to Alzheimer's Dementia 24 Months Before Probable Diagnosis

✓ Peer-reviewed alzhub usefulness score 49 out of 100. Frontiers in aging neuroscience 2018-05-24

There is no disease-modifying treatment currently available for AD, one of the more impacting neurodegenerative diseases affecting more than 47.5 million people worldwide. 1 key finding →

Participants: 200 Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Use of Speech Analyses within a Mobile Application for the Assessment of Cognitive Impairment in Elderly People

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Current Alzheimer research 2018-01-01

Our results indicate the potential value of vocal analytics and the use of a mobile application for accurate automatic differentiation between SCI, MCI and AD. 3 key findings →

Participants: 165 Evidence: low

Full summary, score breakdown and related studies → Original source Full text may need a subscription

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18 F-FDG PET of the Brain

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Radiology 2018-11-06

By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. 3 key findings →

Participants: 1,002 Evidence: low

Full summary, score breakdown and related studies → Original source

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks

✓ Peer-reviewed alzhub usefulness score 48 out of 100. NeuroImage. Clinical 2018-12-18

We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. 5 key findings →

Design: cross-sectional Evidence: low

Full summary, score breakdown and related studies → Original source

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

✓ Peer-reviewed alzhub usefulness score 48 out of 100. IEEE transactions on bio-medical engineering 2018-09-12

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlated. 1 key finding →

Participants: 1,984 Evidence: low

Full summary, score breakdown and related studies → Original source

Dysfunction of Cerebrovascular Endothelial Cells: Prelude to Vascular Dementia

✓ Peer-reviewed alzhub usefulness score 45 out of 100. Frontiers in aging neuroscience 2018-11-16

Vascular dementia (VaD) is the second most common type of dementia after Alzheimer's disease (AD), characterized by progressive cognitive impairment, memory loss, and thinking or speech problems. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images

✓ Peer-reviewed alzhub usefulness score 45 out of 100. Scientific reports 2018-04-09

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia

✓ Peer-reviewed alzhub usefulness score 44 out of 100. Scientific reports 2018-09-05

Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

✓ Peer-reviewed alzhub usefulness score 44 out of 100. IEEE reviews in biomedical engineering 2018-12-11

Dementia, a chronic and progressive cognitive declination of brain function caused by disease or impairment, is becoming more prevalent due to the aging population. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Full text may need a subscription

Identification of Mild Cognitive Impairment From Speech in Swedish Using Deep Sequential Neural Networks

✓ Peer-reviewed alzhub usefulness score 42 out of 100. Frontiers in neurology 2018-11-15

While people with mild cognitive impairment (MCI) portray noticeably incipient memory difficulty in remembering events and situations along with problems in decision making, planning, and finding their way in familiar environments, detailed neuropsychological assessments also indicate deficits in language performance. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

✓ Peer-reviewed alzhub usefulness score 41 out of 100. IEEE transactions on pattern analysis and machine intelligence 2018-12-21

Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided diagnosis of neurodegenerative disorders, e.g., Alzheimer's disease (AD), due to its sensitivity to morphological changes caused by brain atrophy. 5 key findings →

Evidence: moderate

Full summary, score breakdown and related studies → Original source

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Where “Free full text” comes from

Free full text links and the Full text may need a subscription label come from Unpaywall, Europe PMC and OpenAlex records of free copies, checked 10 Oct 2026. A study with neither is unknown, not paywalled. Show only studies that are free to read

How the 0–100 score works — and why some entries are capped

This is alzhub's own score. It is not an official metric, not an impact factor, and no journal, publisher or ranking body endorses it. We built it so that a reader who is not a scientist can tell a landmark trial from a conference abstract without having to already know the difference. Every point comes from one of 20 components, all of them printed on the study itself, so you can disagree with our arithmetic rather than having to trust the total.

  • Journal tier up to 10 pts
  • Journal's citation record up to 4 pts
  • Study design up to 12 pts
  • Strength of evidence up to 5 pts
  • Peer-review validation up to 10 pts
  • How recent up to 5 pts
  • Sample size up to 4 pts
  • Effect reported up to 3 pts
  • Studied in people up to 3 pts
  • Randomised / blinded up to 2 pts
  • Times cited up to 7 pts
  • Citations per year up to 5 pts
  • Impact for its field and year up to 6 pts
  • Cited by studies here up to 6 pts
  • Still being cited up to 4 pts
  • Senior author's track record up to 4 pts
  • Institution's track record up to 3 pts
  • Multi-centre collaboration up to 3 pts
  • Indexed in PubMed up to 2 pts
  • Free to read up to 2 pts

Journals are placed in ordered tiers, never given a numeric impact factor — we could not verify current impact factors from a source we control, and an invented one would be worse than none. Tier 1 is the top-tier general journals (NEJM, The Lancet, JAMA, Nature, Science, Nature Medicine); tier 2 is the leading specialty journals; tier 3 is every other peer-reviewed journal. A separate part scores how much the journal's own papers are cited, which tells the tier-3 journals apart.

Two rules we don't bend. First, we never fill in a missing value: if a record does not state a sample size or a design, that component scores zero, and if we simply have no data for a part, such as a citation count, that part is left out and the study is scored on the parts we could check. The study card says which. Second, anything that is not a peer-reviewed article is capped at 16/100 and carries a warning chip — so a conference abstract or a company press release can never outrank a peer-reviewed paper, no matter how good it looks.

We rank a rigorous null result — a good trial showing that something does not work — above an early positive finding. Someone deciding whether to buy a supplement is served by that, and the rigour is already counted by the design and journal components.

The score is computed from the published data alone and is reproducible: the same file always yields the same numbers.

See the whole rubric drawn out → — four charts covering all 28,180 studies: how the scores are spread and where the cap bites, which of the 20 components the library is strong and weak on, which subjects rest on stronger evidence, and what kinds of study each subject is actually built from.

What this library is — and isn't

This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 28,180 records, built mostly from automated pulls of Europe PMC (61.7% of the library) and OpenAlex (18.1%), plus smaller pulls from PubMed, Crossref and medRxiv. If a study, a drug, or a finding isn't here, that is not evidence it doesn't exist in the literature — it may simply not have been pulled in yet.

1,034 records (3.7% of the library) are not peer-reviewed — 962 of those are preprints posted before any journal review, and the rest are conference abstracts, regulatory notices and reports. Every study card on this page states its status plainly, and the score above is capped for anything that isn't a peer-reviewed article.

See the full, machine-readable breakdown of this library's coverage →

Newest studies, as a dated timeline →    Atom feed