Fractional CO2 laser in the treatment of nail psoriasis: how can it help?

Treating nail psoriasis is often a time-consuming challenge with an unsecure outcome. Response to the treatment is variable and relapses are common. Systemic treatments have multiple systemic side effects and lack of the patient compliance makes intra-lesional therapies not the best choice for treatment of nail psoriasis. We aimed to evaluate and compare the efficacy and side effects of methotrexate versus calcipotriol plus betamethasone two-compound formula when applied topically to psoriatic nails after fractional CO2 laser. This comparative pilot study included 20 patients with nail psoriasis. One side was treated with fractional CO2 laser followed by the application of topical methotrexate (Group A) and the other side with fractional CO2 laser followed by topical (Calcipotriol 0.05 mg/gm + Betamethasone 0.5 mg/gm) (Group B). 4 sessions were done, once every 2 weeks. There was a high statistical significant decrease in total NAPSI score in group A at 1(P = 0.000) and 2 months (P = 0.000). There was a high statistical significant decrease in total NAPSI score in group B at 1(P = 0.001) and 2 months (P = 0.001). There was no statistical significant difference regarding total NAPSI score between both group A and B at 0 (P = 0.271), 1(P = 0.513) and 2 months (P = 0.647). Combined fractional CO2 laser with either topical MTX or topical betamethasone plus calcipotriol two-compound formula is effective treatment for nail psoriasis.

Breast Cancer Diagnosis in Digital Mammography Images Using Automatic Detection for the Region of Interest.

BACKGROUND: One of the early screening methods of breast cancer that is still used today is mammogram due to its low cost. Unfortunately, this low cost accompanied with low performance rate also. METHODS: The low performance rate in mammograms is associated with low capability in determining the best region from which the features are extracted. Therefore, we offer an automatic method to detect the Region of Interest in the mammograms based on maximizing the area under receiver operating characteristic curve utilizing Genetic Algorithms. The proposed method had been applied to the MIAS mammographic database, which is widely used in literature. Its performance had been evaluated using four different classifiers; Support Vector Machine, Naïve Bayes, K-Nearest Neighbor and Logistic Regression classifiers. RESULTS & CONCLUSION: The results showed good classification performances for all the classifiers used due to the rich information contained in the features extracted from the automatically selected Region of Interest.

Modified Mahalanobis Taguchi System for Imbalance Data Classification.

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA).