| Technical Name | End to End Prognosis Foreseer: One Click Prediction for Early Brain Tumor Recurrence using MRI Deep Analysis | ||
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| Project Operator | National Taiwan University | ||
| Project Host | 許哲瑜 | ||
| Summary | Emerging evidence proved the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) against brain metastases of non small cell lung cancer (NSCLC). The study aimed to develop and validate a deep neural network (DNN) based non-invasive classifier to distinguish between the brain metastases from EGFR-mutant and wild-type NSCLC. |
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| Scientific Breakthrough | Brain metastases from EGFR-mutant or wide-type NSCLC can be classified using DNN assisted MR imaging analysis. The non-invasive diagnostic and prognostic approach have potential role in precision therapy cancer treatment for NSCLC brain metastasis. |
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| Industrial Applicability | Brain metastases from EGFR-mutant or wide-type NSCLC can be classified using DNN assisted MR imaging analysis. The non-invasive diagnostic and prognostic approach have potential role in precision therapy cancer treatment for NSCLC brain metastasis. |
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| Keyword | Brain cancer imaging AI cancer data a deep neural network (DNN) non small cell lung cancer (NSCLC), metastasis brain analysis | ||
- claireliu@ncts.ntu.edu.tw
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