## 2 Materials and Methods  
To achieve the aims of our study, the clinical charts, operation logs, CT scans, and pathology reports of 150 patients operated on in a single thoracic surgery clinic were reviewed by five thoracic surgeons. The data were collected at the Thoracic Surgery Clinic from the Emergency Municipal Clinical Hospital Timisoara, the only such specialized clinic in the Banat region of Romania, serving a population of about 1.5 million people, see [[https://www.spitalul-municipal-timisoara.ro/](https://www.spitalul-municipal-timisoara.ro/)]([https://www.spitalul-municipal-timisoara.ro/](https://www.spitalul-municipal-timisoara.ro/)), (accessed on 1 November 2021). These 150 patients were all anonymized, and the data recorded during the review was used to train  
Figure 1: Overall processing steps of the intelligent thoracic diagnosis assistance system. the machine to recognize lung nodules and establish their nature (malignant or benign) based on the image characteristics of the identified nodules and clinical data, along with the pathology reports that either confirmed or informed a cancer diagnosis. When a patient is suspected of suffering from lung cancer disease, they are usually directed to a thoracic surgery clinic, where a thoracic surgeon evaluates the patient's history, current health status, age, smoking status, and most importantly, a thoracic CT scan of the patient. The goal of the first examination is to determine if the patient has a high probability of lung malignancy and if so, they establish the clinical stage of the disease and define the treatment strategy--surgery followed by chemotherapy and/or radiation therapy. To set a correct clinical diagnosis, a surgeon has to evaluate numerous factors. These factors can often be overlooked if the surgeon has little experience. This experience bias could be amplified if the CT scan is evaluated and interpreted by an inexperienced radiologist as well. Since our purpose is to avoid these biases, we have constructed the training set in the form of a knowledge base. For the knowledge base, we considered a total number of 16 clinical (a-f) and imaging (f-p) factors that are associated with a higher cancer probability, as follows:  
1. Age: it is known that lung cancer has a greater incidence after the age of 45 years [7]. 2. Gender (Sex): so far, there is a higher incidence of lung cancer observed in men compared to women in all countries, regardless of the country's development status [8]. 3. Smoking status: it is well proven in the literature that smokers have a very high risk of lung cancer compared to non-smokers [9]. 4. Exposure: the scientific literature demonstrated the role of passive smokers [10; 11; 12; 13]. Furthermore, exposure to microparticles and pollutants has a direct role in lung cancer etiology [14; 15; 16; 17]. 5. Medical history (Historic): refers to prior chronic lung illness that could be related to lung cancer, such as tuberculosis [18; 19; 20] or prior chemotherapy [21] that could be the main cause of malignant transformation of the lung cells. 6. Number of nodules (NoNoduls): CT scan may show a single solitary lung nodule, but in many patients, the nodule can associate with one or more extra nodules in the same lobe or lung, suggesting malignancy or metastatic disease. The imaging characteristics of the nodules are very important and will be discussed below. 7. Localization (PeHi): central localization is associated with a higher prevalence of cancer as opposed to peripheral nodules
8. Size: [PERSON] et al. proved the relationship between the size of the solitary pulmonary nodule (SPN) and malignancy rates: 1% for less than 5 mm, 6-28% between 5 to 10 mm, and 64-82% for SPN larger than 2 cm [22]. 9. Calcification: it is usually a sign of benign disease.