ArticleCurrent medical imaging reviews2017
Decision Support System for Lymphoma Classification.
Article in Current medical imaging reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 6 citations in OpenAlex.
- Application of Machine Learning in Developing Decision-Making Support Models for Decompressed Vertebroplasty.Healthcare (Basel, Switzerland) · 2022Article
- Two-way detection of image features and immunolabeling of lymphoma cells with one-step microarray analysis.Biomicrofluidics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The diffuse lymphoma is a malignant tumor of lymphoid tissues. It is associated with abnormal, unlimited and uncontrolled proliferation of lymphoid cells. Until now, expert pathologists have identified diffuse lymphoma cells disease manually. This paper introduces automatic system with a friendly user interface to differentiate between the categories of the diffuse lymphoma cells. This research is based on the morphological features such as size, perimeter and circularity. The cell size is a critical element in the classification of diffuse lymphoma according to international formulation standards. Therefore, the applied procedures identify lymphoid cell population in digital microscopic images. The cells are classified using their morphological data according to the characteristics of each cell such as: circularity, perimeter, area, and color density. The number of cells is taken into consideration in the developed approach. Image processing techniques are applied to digital microscopic images to measure morphological parameters and to overcome image problems such as overlapping and cell distortion that affect the sensitivity of the measured data. The developed procedures help the pathologists to come to a decision regarding the classification of diffuse lymphoma. Moreover, it can be used to train medical students and young pathologists.
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.