Application of deep convolutional neural networks in the diagnosis of laryngeal squamous cell carcinoma based on narrow band imaging endoscopy / 中华耳鼻咽喉头颈外科杂志

Objective: To explore the possibility of using artificial intelligence (AI) technology based on convolutional neural network (CNN) to assist the clinical diagnosis of laryngeal squamous cell carcinoma (LSCC) through deep learning algorithm. Methods: A deep CNN was developed and applied in narrow band imaging (NBI) endoscopy of 4 799 patients with laryngeal lesions, including 3 168 males and 1 631 females, aged from 21 to 87 years, from 2015 to 2017 in Beijing Tongren Hospital, Capital Medical University. A simple randomization method was used to select the laryngeal NBI images of 2 427 patients (1 388 benign lesions and 1 039 LSCC lesions) for the training and correction the CNN model. The remaining laryngeal NBI images of 2 372 patients (including 1 276 benign lesions and 1 096 LSCC lesions) were used as validation data set to compare performance between CNN and otolaryngologists. SPSS 21.0 software was used for Chi-square test to calculate the accuracy, sensitivity and specificity of AI and otolaryngologists. The area under the curve (AUC) of receiver operating curve (ROC) was used to evaluate the diagnostic ability of the algorithm for NBI images. Results: The accuracy, sensitivity and specificity for NBI predictions were respectively 90.91% (AUC=0.96), 90.12% and 91.53%, which were equivalent to those for otolaryngologists' predictions (accuracy, sensitivity and specificity were (91.93±3.20)%, (91.33±3.25)% and (93.02±2.59)%, t values were 0.64, 0.75 and 1.17, and P values were 0.32, 0.28 and 0.21, respectively). The diagnostic efficiency of CNN was significantly higher than that of otolaryngologists (0.01 vs. 5.50, t =9.15, P<0.001). Conclusion: AI based on deep CNN is effective for using in the laryngeal NBI image diagnosis, showing a good application prospect in the diagnosis of LSCC.

Study on Soil Characteristics of High_mortality Area of Esophageal Cancer in Three Gorge Dam Region / 环境与健康杂志

Objective To study soil environment characteristics of high_mortality areas of esophageal cancer in Three Gorge dam region. Methods To contrast the disparity of soil type,soil use,and basic characteristics,in particular microelement contents in high_mortality area and low_mortality area of esophageal cancer. Results Calcareous purple soils distributed dominantly in high_mortality area,and soil pH and CaCO3 content was high,and soil fertility low. While paddy soils occupyed mainly in low_mortality area,and pH and CaCO3 content was low however soil fertility high.Moreover,the microelement contents in soils in high_mortality area were lower than those in low_mortality area apparently. Conclusion Mortality of esophageal cancer was closely relative to the contents of some microelements in the soil environment.