Evidence map›Paper›PMID 38573545›Full record

ReviewMolecular biotechnology2025

The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

Raghu Aswathy, Sundaravadivelu Sumathi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
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

2 authors.

Raghu AswathyDepartment of Biochemistry, Biotechnology and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Bharathi Park Rd, Near Forest College Campus, Saibaba Colony, Coimbatore, Tamil Nadu, 641043, India.
Sundaravadivelu SumathiDepartment of Biochemistry, Biotechnology and Bioinformatics, Avinashilingam Institute for Home Science and Higher Education for Women, Bharathi Park Rd, Near Forest College Campus, Saibaba Colony, Coimbatore, Tamil Nadu, 641043, India. sumathi_bc@avinuty.ac.in.ORCID http://orcid.org/0000-0002-0041-1913

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer (CC) continues to be a major worldwide health concern, profoundly impacting the lives of countless females worldwide. In low- and middle-income countries (LMICs), where CC prevalence is high, innovative, and cost-effective approaches for prevention, diagnosis, and treatment are vital. These approaches must ensure high response rates with minimal side effects to improve outcomes. The study aims to compile the latest developments in the field of CC, providing insights into the promising future of CC management along with the research gaps and challenges. Integrating biotechnology and artificial intelligence (AI) holds immense potential to revolutionize CC care, from MobileODT screening to precision medicine and innovative therapies. AI enhances healthcare accuracy and improves patient outcomes, especially in CC screening, where its use has increased over the years, showing promising results. Also, combining newly developed strategies with conventional treatment options presents an optimal approach to address the limitations associated with conventional methods. However, further clinical studies are essential for practically implementing these advancements in society. By leveraging these cutting-edge technologies and approaches, there is a substantial opportunity to reduce the global burden of this preventable malignancy, ultimately improving the lives of women in LMICs and beyond.

Indexed as

Artificial IntelligenceBiotechnologyEarly Detection of CancerUterine Cervical NeoplasmsFemaleHumansPrecision MedicineCervical cancerEarly detectionHuman papillomavirus (HPV)Liquid-based cytologyNext-generation sequencing (NGS)RNA sequencing (scRNA-seq)

Identifiers

What OpenQuestion holds

Textmetadata
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.