Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis is a research paper published in Journal of Biomedical Science (2024). On theSindex it has a DataRank of 0. It has been cited 9 times.
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Lung Cancer SPORE
Grant: P50-CA070907
NCI NIH HHS
Grant: P50 CA070907
National Institutes of Health
Grant: 3P50CA070907-02S1
UNIVERSITY OF TEXAS--SPORE IN LUNG CANCER
FWCI
2.33
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 4 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 4 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 1 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 2 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 3 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 1 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 2 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis
Additional file 3 of Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis