AbstractBackground: Lung cancer persist to be a top motive of cancer-related fatalities around the globe. Timely analysis is essential for boosting survival quotes, and chest X-rays (CXR) have served as a normally utilized diagnostic approach for detecting lung irregularities, inclusive of cancer. Nonetheless, the translation of CXR is regularly subjective and prone to human errors. Recent tendencies in artificial intelligence (AI) have proven the capacity to improve diagnostic precision and effectiveness. This research seeks to assess the effectiveness of AI inside the early identity of lung cancer via chest X-rays and to analyze its diagnostic precision between male and lady sufferers.
Objectives: The fundamental goal of this research changed into to assess the capability of AI in identifying lung most cancers thru chest X-rays, focusing on sensitivity, specificity, accuracy, and predictive values. The secondary aim turned into to assess if there are versions in AI effectiveness among male and woman patients.
Methodology: This retrospective study passed off at Tikrit Teaching Hospital, positioned in Tikrit City, Iraq, in January 2024. An overall of 250 sufferers participated, comprising 125 adult males (50%) and 125 women (50%). The age of the patients varied between 40 and 80 years, and the institution comprised each smokers and non-smokers. The AI version applied became tailored to discover lung cancer-related traits in chest X-rays, and its effectiveness was evaluated against conventional radiologist interpretation. The studies assessed the sensitivity, specificity, accuracy, wonderful predictive price (PPV), and bad predictive fee (NPV) of the AI model in male and woman sufferers.
Results: The findings of this research showed the remarkable potential of the AI model to become aware of lung most cancers thru chest X-rays in each male and lady patient populations. The AI model established sturdy sensitivity, specificity, accuracy, and predictive values for sufferers of each genders. Nevertheless, the version confirmed a modest benefit in male patients, specifically regarding sensitivity, specificity, and AUC. This is probably because of gender-based totally versions in tumor developments, like size and location, which can influence the model's capability to perceive lung most cancers. Nonetheless, the AI version showed sturdy diagnostic abilities, emphasizing its capability as a reliable tool for the early identity of lung cancer in both male and girl corporations.
Conclusion: The research shows that AI may also function a treasured aid for assisting radiologists discover lung cancer at an early stage, resulting in better affected person consequences. The findings similarly emphasize AI's potential to limit diagnostic errors and beautify the performance of the diagnostic system, in particular in useful resource-restricted environments. Additional studies related to large pattern sizes and sundry patient demographics is essential to validate those consequences and look into the wider medical makes use of AI in lung cancer screening.
