ReviewCytoJournal2022
Artificial neural network in diagnostic cytology.
Review in CytoJournal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 28 citations in OpenAlex.
- Transfer Learning in Convolutional Neural Network to Differentiate Follicular Adenoma Versus Follicular Carcinoma of Thyroid on Aspiration Cytology Material.Cytopathology : official journal of the British Society for Clinical Cytology · 2026Article
- Impact of Magnification, Image Type, and Number on Convolutional Neural Network Performance in Differentiating Canine Large Cell Lymphoma From Non-Lymphoma via Lymph Node Cytology.Veterinary clinical pathology · 2025Article
- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Bringing AI to Clinicians: Simplifying Pleural Effusion Cytology Diagnosis with User-Friendly Models.Diagnostics (Basel, Switzerland) · 2025Article
- Neural Network-Aided Milk Somatic Cell Count Increase Prediction.Veterinary sciences · 2025Article
- Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2024Article
- Construction and validation of a joint diagnosis model based on random forest and artificial intelligence network for hepatitis B-related hepatocellular carcinoma.Translational cancer research · 2024Article
- Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid.Cells · 2023Article
- Digital Media Teaching and Effectiveness Evaluation Integrating Big Data and Artificial Intelligence.Computational intelligence and neuroscience · 2022Article
- A Critical Review of Deep Learning Technique and Its Applications in Clinical Cytology.Journal of cytologyReview
- Ensemble Learning to Categorize the Bethesda System of Reporting of Cervical Cytology.Journal of cytologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The artificial neural network (ANN) is a computer software design or model that simulates the biological neural network of the human brain. Instead of biological neurons, ANN is composed of many layers of nodes that carry the signal and process it to make the final decision. ANN is a modern technology that is widely used in different fields of science. The ANN is reshaping the medical system and the various areas of pathology. In this paper, the basic concept and applications of ANN in cytology have been discussed. In this paper, the various articles published on ANN in the field of cytology have been systemically reviewed. The ANN is relatively less used in cytology. After introducing convolutional neural network and whole slide scanners in the commercial market, it is now essential to have thorough knowledge in this field to start diagnostic application of ANN.
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.