Abstract
Lung cancer is one of the most common and lethal cancers globally, and early detection plays a crucial role in improving patient survival. Traditional diagnostic techniques rely on manual analysis of medical images, which can be time-consuming and susceptible to human error. This paper discusses the use of AI tools in the early detection of lung cancer. This can be used to improve the detection accuracy significantly as against conventional methods, thereby allowing AI assistance to radiologists to make more accurate and timely diagnoses. The framework further allows it to be scaled and adapted for different imaging modalities to be implemented in real clinical settings. This research will show the transformative impacts that AI has on healthcare, especially against diseases like lung cancer, where early detection is key.
Published Version
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