Evidence map›Paper›PMID 39789283›Full record

ReviewClinical and experimental medicine2025

Recent developments and future directions in point-of-care next-generation CRISPR-based rapid diagnosis.

Youssef M Hassan, Ahmed S Mohamed, Yaser M Hassan, Wael M El-Sayed

Abstract readReview
In one paragraph

Review in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
–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

43 citing papers in PubMed.

  1. Review
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  6. Machine Learning for CRISPR-Based Diagnostics.International journal of molecular sciences · 2026
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  9. Article
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  11. Integrating metagenomics and metatranscriptomics intoThe Journal of general virology · 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

4 authors.

Youssef M HassanDepartment of Zoology, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.ORCID http://orcid.org/0009-0005-3615-4137
Ahmed S MohamedBiotechnology Program, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.ORCID http://orcid.org/0009-0007-1093-2695
Yaser M HassanBiotechnology Program, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt.ORCID http://orcid.org/0009-0008-0061-739X
Wael M El-SayedDepartment of Zoology, Faculty of Science, Ain Shams University, Abbassia, Cairo, 11566, Egypt. wael_farag@sci.asu.edu.eg.ORCID http://orcid.org/0000-0002-3622-1417

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The demand for sensitive, rapid, and affordable diagnostic techniques has surged, particularly following the COVID-19 pandemic, driving the development of CRISPR-based diagnostic tools that utilize Cas effector proteins (such as Cas9, Cas12, and Cas13) as viable alternatives to traditional nucleic acid-based detection methods. These CRISPR systems, often integrated with biosensing and amplification technologies, provide precise, rapid, and portable diagnostics, making on-site testing without the need for extensive infrastructure feasible, especially in underserved or rural areas. In contrast, traditional diagnostic methods, while still essential, are often limited by the need for costly equipment and skilled operators, restricting their accessibility. As a result, developing accessible, user-friendly solutions for at-home, field, and laboratory diagnostics has become a key focus in CRISPR diagnostic innovations. This review examines the current state of CRISPR-based diagnostics and their potential applications across a wide range of diseases, including cancers (e.g., colorectal and breast cancer), genetic disorders (e.g., sickle cell disease), and infectious diseases (e.g., tuberculosis, malaria, Zika virus, and human papillomavirus). Additionally, the integration of machine learning (ML) and artificial intelligence (AI) to enhance the accuracy, scalability, and efficiency of CRISPR diagnostics is discussed, alongside the challenges of incorporating CRISPR technologies into point-of-care settings. The review also explores the potential for these cutting-edge tools to revolutionize disease diagnosis and personalized treatment in the future, while identifying the challenges and future directions necessary to address existing gaps in CRISPR-based diagnostic research.

Indexed as

CRISPR-Cas SystemsMolecular Diagnostic TechniquesPoint-of-Care TestingCOVID-19HumansSARS-CoV-2Artificial intelligenceBiosensing technologiesCRISPR-Cas systemsDisease detectionMachine learningMicrofluidic platformsNucleic acid diagnostics

Identifiers

PMID39789283
PMCPMC11717804

What OpenQuestion holds

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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.