Innovative laboratory techniques shaping cancer diagnosis and treatment in developing countries

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 8, 2025

Abstract Cancer is a major global health challenge, with approximately 19.3 million new cases and 10 deaths estimated by 2020. Laboratory advancements in cancer detection have transformed diagnostic capabilities, particularly through the use of biomarkers that play crucial roles risk assessment, therapy selection, disease monitoring. Tumor histology, single-cell technology, flow cytometry, molecular imaging, liquid biopsy, immunoassays, diagnostics emerged as pivotal tools for detection. The integration artificial intelligence, deep learning convolutional neural networks, has enhanced accuracy data analysis capabilities. However, developing countries face significant challenges including financial constraints, inadequate healthcare infrastructure, limited access to advanced technologies. impact COVID-19 further complicated management resource-limited settings. Future research should focus on precision medicine early diagnosis sophisticated laboratory techniques improve prognosis outcomes. This review examines evolving landscape detection, focusing breakthroughs limitations countries, while providing recommendations advancing tumor resource-constrained environments.

Language: Английский

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Pancreatic Cancer Detection using Machine and Deep Learning Techniques

2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM), Journal Year: 2022, Volume and Issue: unknown, P. 151 - 155

Published: Feb. 23, 2022

Despite substantial research, pancreatic cancer has a terrible prognosis by having survival rate of five years only. The premise behind early detection and better is that more people will benefit from possible treatment. In general health care, machine deep learning algorithms have shown to be viable tool classify or detect the risk cancer. As result, in this work, we looked into various researchers' methods for diagnosing using models. addition, report highlighted their achievements obstacles remain sector. We incorporated our evaluation numerous strategies available make some conclusions.

Language: Английский

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Prediction Performance of Deep Learning for Colon Cancer Survival Prediction on SEER Data

BioMed Research International, Journal Year: 2022, Volume and Issue: 2022, P. 1 - 12

Published: June 16, 2022

Colon and rectal cancers are the most common kinds of cancer globally. is more prevalent in men than women. Early detection increases likelihood survival, treatment significantly eradicating disease. The Surveillance, Epidemiology, End Results (SEER) programme an excellent source domestic statistics. SEER includes nearly 30% United States population, covering various races geographic locations. data made public via website when a limited-use agreement form submitted approved. We investigate from programme, specifically colon statistics, this study. Our objective to create reliable survival conditional prediction algorithms. In study, we have presented overview diagnosis methods treatments used cure cancer. This paper presents analysis performance multiple deep learning approaches. models thoroughly examined discover which algorithm surpasses others, followed by investigation network's accuracy. simulation outcomes indicate that automated can predict patient survival. Deep autoencoders displayed best attaining 97% accuracy 95% area under curve-receiver operating characteristic (AUC-ROC).

Language: Английский

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An Investigational Approach for the Prediction of Gastric Cancer Using Artificial Intelligence Techniques: A Systematic Review

Archives of Computational Methods in Engineering, Journal Year: 2022, Volume and Issue: 29(6), P. 4379 - 4400

Published: April 19, 2022

Language: Английский

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A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics

Journal of Cancer Research and Clinical Oncology, Journal Year: 2023, Volume and Issue: 149(15), P. 14365 - 14408

Published: Aug. 4, 2023

Language: Английский

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