A Study of Diagnostic Accuracy Using a Chemical Sensor Array and a Machine Learning Technique to Detect Lung Cancer.

Lung cancer is the leading cause of cancer death around the world, and lung cancer screening remains challenging. This study aimed to develop a breath test for the detection of lung cancer using a chemical sensor array and a machine learning technique. We conducted a prospective study to enroll lung cancer cases and non-tumour controls between 2016 and 2018 and analysed alveolar air samples using carbon nanotube sensor arrays. A total of 117 cases and 199 controls were enrolled in the study of which 72 subjects were excluded due to having cancer at another site, benign lung tumours, metastatic lung cancer, carcinoma in situ, minimally invasive adenocarcinoma, received chemotherapy or other diseases. Subjects enrolled in 2016 and 2017 were used for the model derivation and internal validation. The model was externally validated in subjects recruited in 2018. The diagnostic accuracy was assessed using the pathological reports as the reference standard. In the external validation, the areas under the receiver operating characteristic curve (AUCs) were 0.91 (95% CI = 0.79⁻1.00) by linear discriminant analysis and 0.90 (95% CI = 0.80⁻0.99) by the supportive vector machine technique. The combination of the sensor array technique and machine learning can detect lung cancer with high accuracy.

A New Technique to Increase Reliability in Measuring the Axis of Bone.

Measuring bone angles is an important method for diagnosing disease and predicting the prognosis in orthopedics. Traditionally, the angle is measured using lines drawn manually and adjusted by the naked eye. The purpose of the present study was to propose new methods to measure the bone angles formed by the axes of the calcaneus with good reliability and low operational error. The 2 new methods used linear regression analysis of the points inside and on the "envelope" line. The traditional method used the vector of the lines drawn for calculation. Digital radiographs of the lateral view of the feet from 51 patients were collected, and the angles were measured using these 3 methods. Next, we analyzed the reliability, differences, and correlations of these 3 methods. The intra- and interobserver comparisons revealed significant differences between the results of the 2 new methods and those of the traditional method. In addition, the new methods had greater reliability and better intra- and interobserver correlations than did the traditional method. We suggest that these 2 new methods to measure bone axis should be added to the Picture Archiving and Communication System to obtain more reliable and standardized data in clinical practice and for future research purposes.