ArticleComputational and structural biotechnology journal2024
Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Artificial intelligence for colposcopic and cytological image analysis in early cervical cancer detection.iScience · 2026Review
- Systems Analysis of miRNA-Mediated Host Regulatory Response in HPV-Associated Cervical Malignancy.Computational and structural biotechnology journal · 2026Article
- Advancements in artificial intelligence for cancer diagnosis and prognosis prediction: current applications and emerging opportunities.Frontiers in cell and developmental biology · 2026Review
- Patient acceptability of CITOBOT for cervical cancer screening: A mixed-method study.PloS one · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cervical cancer remains a leading cause of mortality in its invasive stages, presenting a significant global public health challenge, particularly in low- and middle-income countries. Despite technological advancements that have improved the quality of cervical images captured during visual inspections, several challenges persist. This article presents key findings from the CITOBOT-COL translational research project, a large-scale initiative focused on designing CITOBOT as a portable cervical cancer screening device. We detail the comprehensive technological development of CITOBOT, guided by a human-centered design approach, smart prototyping, and the integration of AI. Over four design iterations, we developed and refined CITOBOT v4, a portable device. Prototypes were validated through focus groups and testing by experts in cervical cancer prevention, gynecology, nursing, software, artificial intelligence, computer engineering, and public health, utilizing various anatomical models at the Simulated Hospital Laboratory of Pontificia Universidad Javeriana Cali, Colombia. Additionally, we developed AI algorithms using the Inception V3 network, optimized with Transfer Learning and Fine Tuning, for cervical image classification and offline-operating software that guides the physician through the examination and provides a risk assessment for cervical cancer. Feedback was crucial in assessing and refining the device's functionality, focusing on capturing high-quality cervical images. The development of CITOBOT v4 highlights the importance of fostering innovation in resource-limited settings, offering an effective solution to improve cervical cancer screening and potentially save lives in vulnerable communities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.