Evidence map›Paper›PMID 38958517›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Revolutionary Point-of-Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies.

Fatemeh Haghayegh, Alireza Norouziazad, Elnaz Haghani, Ariel Avraham Feygin, Reza Hamed Rahimi, Hamidreza Akbari Ghavamabadi, Deniz Sadighbayan, Faress Madhoun, Manos Papagelis, Tina Felfeli and 1 more

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  14. AI-Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Fatemeh HaghayeghLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Alireza NorouziazadLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Elnaz HaghaniLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Ariel Avraham FeyginLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Reza Hamed RahimiLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Hamidreza Akbari GhavamabadiLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Deniz SadighbayanDepartment of Biology, Faculty of Science, York University, Toronto, ON, M3J 1P3, Canada.
Faress MadhounLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.
Manos PapagelisDepartment of Electrical Engineering and Computer Science (EECS), Lassonde School of Engineering, York University, Toronto, ON, M3J 1P3, Canada.
Tina FelfeliDepartment of Ophthalmology and Vision Sciences, University of Toronto, Ontario, M5T 3A9, Canada.
Razieh SalahandishLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Biomedical Engineering Program, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada.ORCID 0000-0003-1299-1051

Funding

Lassonde Innovation FundNatural Sciences and Engineering Research Council of Canada RGPIN-2023-05091York University
6 · The paper itself

Abstract

Early-stage disease detection, particularly in Point-Of-Care (POC) wearable formats, assumes pivotal role in advancing healthcare services and precision-medicine. Public benefits of early detection extend beyond cost-effectively promoting healthcare outcomes, to also include reducing the risk of comorbid diseases. Technological advancements enabling POC biomarker recognition empower discovery of new markers for various health conditions. Integration of POC wearables for biomarker detection with intelligent frameworks represents ground-breaking innovations enabling automation of operations, conducting advanced large-scale data analysis, generating predictive models, and facilitating remote and guided clinical decision-making. These advancements substantially alleviate socioeconomic burdens, creating a paradigm shift in diagnostics, and revolutionizing medical assessments and technology development. This review explores critical topics and recent progress in development of 1) POC systems and wearable solutions for early disease detection and physiological monitoring, as well as 2) discussing current trends in adoption of smart technologies within clinical settings and in developing biological assays, and ultimately 3) exploring utilities of POC systems and smart platforms for biomarker discovery. Additionally, the review explores technology translation from research labs to broader applications. It also addresses associated risks, biases, and challenges of widespread Artificial Intelligence (AI) integration in diagnostics systems, while systematically outlining potential prospects, current challenges, and opportunities.

Indexed as

BiomarkersEarly DiagnosisPoint-of-Care SystemsWearable Electronic DevicesArtificial IntelligenceHumansMonitoring, PhysiologicBiomarkersAI‐assisted biomarker discoveryhigh‐throughput omics and clinical studyintelligent diagnosticspoint‐of‐care biomarker detection platformsprecision medicineremote disease detectionwearable health monitoring

Identifiers

PMID38958517
PMCPMC11423253

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.