A Method for Optimal Detection of Lung Cancer Based on Deep Learning Optimized by Marine Predators Algorithm.

Lung cancer is the uncontrolled growth of cells in the lung that are made up of two spongy organs located in the chest. These cells may penetrate outside the lungs in a process called metastasis and spread to tissues and organs in the body. In this paper, using image processing, deep learning, and metaheuristic, an optimal methodology is proposed for early detection of this cancer. Here, we design a new convolutional neural network for this purpose. Marine predators algorithm is also used for optimal arrangement and better network accuracy. The method finally applied to RIDER dataset, and the results are compared with some pretrained deep networks, including CNN ResNet-18, GoogLeNet, AlexNet, and VGG-19. Final results showed higher results of the proposed method toward the compared techniques. The results showed that the proposed MPA-based method with 93.4% accuracy, 98.4% sensitivity, and 97.1% specificity provides the highest efficiency with the least error (1.6) toward the other state of the art methods.

Alendronate improves fasting plasma glucose and insulin sensitivity, and decreases insulin resistance in prediabetic osteopenic postmenopausal women: A randomized triple-blind clinical trial.

AIMS/INTRODUCTION: Postmenopausal women receive bisphosphonates for osteoporosis treatment. The effect of these medications on developing diabetes mellitus in prediabetic patients is yet to be investigated. We aimed to determine the effect of alendronate on plasma glucose, insulin indices of postmenopausal women with prediabetes and osteopenia. MATERIALS AND METHODS: The present triple-blind randomized controlled clinical trial included 60 postmenopausal women, aged 45-60 years. All patients were vitamin D sufficient. They were randomly enrolled in intervention (70 mg/week alendronate for 12 weeks) and control (placebo tablet per week for 12 weeks) groups. The morning 8-h fasting blood samples were collected at the baseline and follow-up visits to measure the fasting plasma glucose (mg/dL), insulin and hemoglobin A1c (HbA1c). Plasma glucose and insulin concentration were measured 30, 60 and 120 min after the glucose tolerance test. The Matsuda Index, homeostasis model assessment of insulin resistance, homeostasis model assessment of ß-cell function and the area under the curves of glucose and insulin were calculated. RESULTS: The mean (standard deviation) fasting plasma glucose (102.43 [1.46] mg/dL vs 94.23 [1.17] mg/dL, P = 0.001), 120-min insulin concentration (101.86 [15.70] mU/L vs 72.60 [11.36] mU/L, P = 0.026), HbA1c (5.60 [0.06]% vs 5.40 [0.05]%, P = 0.001), homeostasis model assessment of insulin resistance (3.57 [0.45] vs 2.62 [0.24], P = 0.021) and Matsuda Index (7.7 [0.41] vs 9.2 [0.4], P = 0.001) significantly improved in the alendronate-treated group. There were more statistically significant reductions in fasting plasma glucose (-8.2 [8.63] mg/dL vs -2.5 [14.26] mg/dL, P = 0.002) and HbA1c (-0.2 [0.23]% vs -0.09 [0.26]%, P = 0.015) observed in the alendronate-treated group than the placebo group during the study course, respectively. CONCLUSIONS: Administration of 70 mg/week alendronate improves fasting plasma glucose, HbA1c and insulin indices in postmenopausal women.