Using machine learning approaches for multi-omics data analysis: A review
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
Application of artificial intelligence in lung cancer
Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …
Machine learning: a new prospect in multi-omics data analysis of cancer
Cancer is defined as a large group of diseases that is associated with abnormal cell growth,
uncontrollable cell division, and may tend to im**e on other tissues of the body by different …
uncontrollable cell division, and may tend to im**e on other tissues of the body by different …
Artificial intelligence in metabolomics: A current review
Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics
generates large datasets comprising hundreds to thousands of metabolites with complex …
generates large datasets comprising hundreds to thousands of metabolites with complex …
Machine learning: its challenges and opportunities in plant system biology
Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
Applied machine learning in Alzheimer's disease research: omics, imaging, and clinical data
Alzheimer's disease (AD) remains a devastating neurodegenerative disease with few
preventive or curative treatments available. Modern technology developments of high …
preventive or curative treatments available. Modern technology developments of high …
Multi-omics research strategies in ischemic stroke: A multidimensional perspective
W Li, C Shao, H Zhou, H Du, H Chen, H Wan… - Ageing Research …, 2022 - Elsevier
Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high
rate of death and long-term impairment. Despite years of studies, there are still no stroke …
rate of death and long-term impairment. Despite years of studies, there are still no stroke …
New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review
X Ge, J Gao, R Niu, Y Shi, X Shao, Y Wang… - Frontiers in …, 2023 - frontiersin.org
Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of
cancer-associated deaths. In recent years, significant progress has been achieved in basic …
cancer-associated deaths. In recent years, significant progress has been achieved in basic …
[HTML][HTML] Multiomics and machine learning in lung cancer prognosis
Y Gao, R Zhou, Q Lyu - Journal of thoracic disease, 2020 - ncbi.nlm.nih.gov
Wang et al.(13) presented a method to construct a prediction model of EGFR mutation-
induced drug resistance in lung cancer by combining pathological and demographic data …
induced drug resistance in lung cancer by combining pathological and demographic data …
The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews
HEC Silva, GNM Santos, AF Leite, CRM Mesquita… - Plos one, 2023 - journals.plos.org
Background and purpose In comparison to conventional medical imaging diagnostic
modalities, the aim of this overview article is to analyze the accuracy of the application of …
modalities, the aim of this overview article is to analyze the accuracy of the application of …