The detection of lung cancer is a critical fact or in enhancing patient survival rates. The integration of intelligent computer-aided systems can significantly aid radiologists in this endeavor. The present study centers on the development of a machine learning-oriented methodology aimed at detecting lung cancer through the analysis of text-based medical data extracted from authentic medical reports. The present dataset encompasses a range of machine-learning algorithms that have been utilized for binary classification purposes. The findings of this study indicate the capability of machine learning algorithms in the prompt identification of lung cancer, thereby facilitating enhanced diagnosis and timely intervention.
Hi, please find this recent research applying unsupervised machine learning for early plant diseases detection:
Article Abaxial leaf surface-mounted multimodal wearable sensor for ...
The method could be useful for classifying lung cancer types and also healthy samples.
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