Evidence map›Paper›PMID 36983570›Full record

ArticleJournal of personalized medicine2023

Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis.

DaifAllah D Althubaity, Faisal Fahad Alotaibi, Abdalla Mohamed Ahmed Osman, Mugahed Ali Al-Khadher, Yahya Hussein Ahmed Abdalla, Sadeq Abdo Alwesabi, Elsadig Eltaher Hamed Abdulrahman, Maram Abdulkhalek Alhemairy

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Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

DaifAllah D AlthubaityPediatric Nursing Department, Faculty of Nursing, Najran University, Najran 66441, Saudi Arabia.
Faisal Fahad AlotaibiStrategy Studies and Planning Department, Prince Sultan Medical Military City, Riyadh 13521, Saudi Arabia.
Abdalla Mohamed Ahmed OsmanCommunity and Mental Health, College of Nursing, Najran University, Najran 66441, Saudi Arabia.
Mugahed Ali Al-KhadherNursing College, Najran University, Najran 66441, Saudi Arabia.
Yahya Hussein Ahmed AbdallaNursing College, Najran University, Najran 66441, Saudi Arabia.ORCID 0000-0002-9805-4669
Sadeq Abdo AlwesabiNursing College, Najran University, Najran 66441, Saudi Arabia.ORCID 0000-0002-7075-7880
Elsadig Eltaher Hamed AbdulrahmanNursing College, Najran University, Najran 66441, Saudi Arabia.
Maram Abdulkhalek AlhemairyNursing College, Najran University, Najran 66441, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today.

objectiveDevelop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images.

methodThe prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images.

resultsThe system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue.

conclusionThe computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer.

Indexed as

automatic identificationCADhistopathological imageslung cancerTMATumor

Identifiers

PMID36983570
PMCPMC10051974

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