Research Methods for Health Professionals
Artificial Intelligence in the Early Detection of Lung Cancer
CNHP 6000:
Research Methods for Health Professionals
Jasma Johnson
Introduction
Lung cancer remains one of the leading cancer-related causes of death globally, with a high fatality rate primarily due to late-stage diagnoses.1 Traditional diagnosis techniques, such as imaging and biopsy, are inadequate to diagnose lung cancer at the early stages, which has a far better chance of being treated. Early diagnosis is important because often when diagnosed early, lung cancer can be treated and cured. Nevertheless, the signs of lung cancer are often diverse and nonspecific so that the disease can be masked, and the treatment starts only later. That is why new approaches are needed to improve the effectiveness of early diagnostic tools.
Recent developments in artificial intelligence (AI) have transformed the field of cancer diagnostics and opened up new avenues for the early detection of lung cancer. Several studies have shown AI can assist in diagnosing medical images and patient characteristics more effectively than conventional diagnostics. For example, Daneshkhah et al2 studied AI-assisted optical nanosensing to discover altered chromatin regions linked to lung carcinogenesis. Their findings concluded AI can identify molecular patterns consistent with early-stage lung cancer, which may be used for screening purposes.
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