Lung cancer type classification using differentiator genes

Ramroach, Sterling; John, McCormick; Joshi, Ajay

doi:10.1016/j.genrep.2020.100647

Cited by 5 publications

(4 citation statements)

References 36 publications

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“…We find no significant upregulation of these genes in patients with CCCA with a history of ULs compared with the genes in patients with CCCA without a history of ULs and instead find increased expression of KRTAP19-4 and LCE3D , genes without a known role in fibrosis or aberrant fibrogenesis ( Marshall et al., 2001 ; Sack et al., 2018 ). KRTAP19-4 is instead a protein-encoding gene involved in the formation of disulfide bonds between hair keratins and cysteine residues ( Ramroach et al., 2020 ; Yahagi et al., 2004 ), and LCE3D encodes stratum corneum proteins and belongs to a gene cluster located on human chromosome 1 in the epidermal differentiation complex ( Marshall et al., 2001 ).…”

Section: Discussionmentioning

confidence: 99%

Presence of Uterine Leiomyomas Has No Significant Impact on Gene Expression Profile in the Scalp of Patients with Central Centrifugal Cicatricial Alopecia

et al. 2022

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Discussionmentioning

confidence: 99%

Presence of Uterine Leiomyomas Has No Significant Impact on Gene Expression Profile in the Scalp of Patients with Central Centrifugal Cicatricial Alopecia

et al. 2022

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“…Ramroach et al (2020) [11] proposed an approach that included image pre-processing methods such as median filtering for noise reduction, the MEM algorithm for image segmentation, and feature extraction to identify the area of interest of lung nodules. Lung cancer detection employs the SVM classification.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Hybrid Adaptive Optimization Algorithm Based Wavelet Neural Network for Severity Level Prediction for Lung Cancer Dataset

2024

IJIES

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This study proposes three contributions focused on lung cancer detection and severity level identification. The absence of non-invasive technologies for predicting lung cancer necessitates faster, more efficient, and more accurate classification procedures due to the absence of non-invasive technologies for predicting lung cancer. Creating an automated and intelligent prediction system is crucial for identifying phases and predicting the possibility of a recurrence. The objective is to create an automated detection system for identifying lung cancer using an optimizationfocused deep learning model. We develop an adaptive multi-swarm PSO and combine it with the firefly algorithm to determine the ideal weight values for the Wavelet Neural Network (WNN) model. We use the HAPSO-FFA-WNN method to explore problems with multiple optimal solutions. This study evaluated two lung cancer datasets, and the proposed HAPSO-FFA-WNN model achieved 97.58% accuracy for dataset 1 and 98.54% accuracy for dataset 2. Furthermore, the proposed model achieved better precision, recall, and MCC performance metrics.

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“…It has a signet ring, clear cell and mucinous type, and fetal adenocarcinoma. 13,17 SCLC is a neuroendocrine tumor that tends to present as a central mass with endobracial growth and is strongly associated with smoking. SCLC has cells with a small cytoplasm, a small hyperchromatic nucleus with a chromatin pattern such as "salt and pepper" and a prominent nucleolus.…”

Section: Classificationmentioning

confidence: 99%

Lung Cancer: A Literature Review

Sembiring,

Effendi,

Dillon

et al. 2023

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Lung cancer is a cancer whose onset starts in the lungs where there is an abnormal cell growth that is very fast and uncontrolled. The abnormal cell growth is triggered by deoxyribonucleic acid (DNA) damage, including deletions in the DNA section, inactivation of tumor suppressor genes, activation of proto-oncogenes to oncogenes, the absence of apoptosis, and the activity of the telomerase enzyme. Lung cancer is initiated by oncogeneous activity and inactivation of tumor suppressor genes. Oncogenes are genes that help cells grow and divide and are believed to cause a person to develop lung cancer. In general, lung cancer is divided into two types, namely non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). World Health Organization (WHO) classifies lung cancer based on histopathology into 4 major cell types, namely SCLC, NSCLC which includes adenocarcinoma, squamous cell carcinoma (SCC), and large cell carcinoma (LCC). The difference between the two is that SCLC has a higher aggressiveness than NSCLC. Cancer treatment is based on the type, size, location and stage of the cancer, as well as the patient's overall condition.

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Lung cancer type classification using differentiator genes

Cited by 5 publications

References 36 publications

Presence of Uterine Leiomyomas Has No Significant Impact on Gene Expression Profile in the Scalp of Patients with Central Centrifugal Cicatricial Alopecia

Presence of Uterine Leiomyomas Has No Significant Impact on Gene Expression Profile in the Scalp of Patients with Central Centrifugal Cicatricial Alopecia

A New Hybrid Adaptive Optimization Algorithm Based Wavelet Neural Network for Severity Level Prediction for Lung Cancer Dataset

Lung Cancer: A Literature Review

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