Applications and techniques of machine learning in cancer classification: A systematic review
The domain of Machine learning has experienced Substantial advancement and
development. Recently, showcasing a Broad spectrum of uses like Computational …
development. Recently, showcasing a Broad spectrum of uses like Computational …
[HTML][HTML] Integrating molecular perspectives: strategies for comprehensive multi-omics integrative data analysis and machine learning applications in transcriptomics …
Simple Summary Recent high-throughput technologies such as transcriptomics, proteomics,
and metabolomics have allowed progress in understanding biological systems at different …
and metabolomics have allowed progress in understanding biological systems at different …
Gene selection with Game Shapley Harris hawks optimizer for cancer classification
Cancer disease has been classified as a perilous disease for humans, being the second
leading cause of death globally. Even advanced-stage diagnosis may not be effective in …
leading cause of death globally. Even advanced-stage diagnosis may not be effective in …
Analyzing Quantum Feature Engineering and Balancing Strategies Effect on Liver Disease Classification
This research aims to improve the accuracy of liver disease classification using Quantum
Feature Engineering (QFE) and the Synthetic Minority Over-sampling Tech-nique and …
Feature Engineering (QFE) and the Synthetic Minority Over-sampling Tech-nique and …
[HTML][HTML] Artificial intelligence and machine learning applications for cultured meat
Cultured meat has the potential to provide a complementary meat industry with reduced
environmental, ethical, and health impacts. However, major technological challenges …
environmental, ethical, and health impacts. However, major technological challenges …
[HTML][HTML] Possible integration of artificial intelligence with photodynamic therapy and diagnosis: A review
Cancer remains a deadly disease with a low median survival rate. The increase in cancer
mortality rates is attributed to limitations in diagnosis, prognosis prediction, and therapeutic …
mortality rates is attributed to limitations in diagnosis, prognosis prediction, and therapeutic …
A novel feature selection algorithm for identifying hub genes in lung cancer
Lung cancer, a life-threatening disease primarily affecting lung tissue, remains a significant
contributor to mortality in both developed and develo** nations. Accurate biomarker …
contributor to mortality in both developed and develo** nations. Accurate biomarker …
[HTML][HTML] Leveraging state-of-the-art ai algorithms in personalized oncology: From transcriptomics to treatment
A Shams - Diagnostics, 2024 - mdpi.com
Background: Continuous breakthroughs in computational algorithms have positioned AI-
based models as some of the most sophisticated technologies in the healthcare system. AI …
based models as some of the most sophisticated technologies in the healthcare system. AI …
Classification of cancer cells and gene selection based on microarray data using MOPSO algorithm
MR Rahimi, D Makarem, S Sarspy, SA Mahdavi… - Journal of Cancer …, 2023 - Springer
Purpose Microarray information is crucial for the identification and categorisation of
malignant tissues. The very limited sample size in the microarray has always been a …
malignant tissues. The very limited sample size in the microarray has always been a …
Machine-Learning-Based Prediction Modelling in Primary Care: State-of-the-Art Review
Primary care has the potential to be transformed by artificial intelligence (AI) and, in
particular, machine learning (ML). This review summarizes the potential of ML and its …
particular, machine learning (ML). This review summarizes the potential of ML and its …