ArticleComputational and mathematical methods in medicine2021
Breast Cancer Calcifications: Identification Using a Novel Segmentation Approach.
Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 7 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
7 citing papers in PubMed, 35 citations in OpenAlex.
- An enhanced denoising system for mammogram images using deep transformer model with fusion of local and global features.Scientific reports · 2025Article
- Retracted: Breast Cancer Calcifications: Identification Using a Novel Segmentation Approach.Computational and mathematical methods in medicine · 2023Article
- Monitoring Cardiovascular Problems in Heart Patients Using Machine Learning.Journal of healthcare engineering · 2023Article
- Face mask recognition system using CNN model.Neuroscience informatics · 2022Review
- Visual bias could impede diagnostic accuracy of breast cancer calcifications.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Effective Image Processing and Segmentation-Based Machine Learning Techniques for Diagnosis of Breast Cancer.Computational and mathematical methods in medicine · 2022Article
- A Lightweight Hybrid Dilated Ghost Model-Based Approach for the Prognosis of Breast Cancer.Computational intelligence and neuroscience · 2022Article
Corrections and comments
- Retraction · 2023-07-19Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/1A1D50CAFD5A64EA0B4CE0BEBC5821
- Retracted
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is a strong risk factor of cancer amongst women. One in eight women suffers from breast cancer. It is a life-threatening illness and is utterly dreadful. The root cause which is the breast cancer agent is still under research. There are, however, certain potentially dangerous factors like age, genetics, obesity, birth control, cigarettes, and tablets. Breast cancer is often a malignant tumor that begins in the breast cells and eventually spreads to the surrounding tissue. If detected early, the illness may be reversible. The probability of preservation diminishes as the number of measurements increases. Numerous imaging techniques are used to identify breast cancer. This research examines different breast cancer detection strategies via the use of imaging techniques, data mining techniques, and various characteristics, as well as a brief comparative analysis of the existing breast cancer detection system. Breast cancer mortality will be significantly reduced if it is identified and treated early. There are technological difficulties linked to scans and people's inconsistency with breast cancer. In this study, we introduced a form of breast cancer diagnosis. There are different methods involved to collect and analyze details. In the preprocessing stage, the input data picture is filtered by using a window or by cropping. Segmentation can be performed using
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.