Background. Venous leg ulcers (VLUs) are a health problem in clinical care. Several options can be employed as adjuvant to standard treatment. Objectives.We have aimed to analyze the effect of standard ulcer care alone with high-frequency ultrasound (HFU) and MIST ultrasound therapy on VLUs. Material and Methods. Ninety patients with VLUs were assigned into the standard treatment, HFU and MIST ultrasound groups. All groups received the standard wound care. In the ultrasound groups, HFU and MIST ultrasound therapy was administered to wounds 3 times per week until the wound healed. Time of complete wound healing was recorded. Wound size, pain, and edema were assessed at baseline and after 2 and 4 months. Also, patients were instructed to contact our clinic monthly, and recurrence of VLUs was recorded for 6 months after complete wound healing. The data was analyzed using a Student's t-test, ANOVA, c
Background. Pilonidal disease is foreign body reactions accompanied by chronic inflammation that most commonly arises in the hair follicles of the natal cleft or other hair-bearing areas. Today, surgical intervention remains the treatment of choice. but surgical treatment is an invasive method with a high failure rate and recurrence. Objectives. The authors' objective was to assess the efficacy of intense pulsed light (IPL) device on pilonidal disease. Material and Methods. This case series study was carried out between 2008 and 2012 on patients with pilonidal sinus in Qazvin university of Iran. All patients received 6 session treatments with IPL hair removal with 4-6 weeks interval until most of the hair was removed. This was repeated 2.5 ± 0.3 years after treatment. In cases with acute phase pilonidal sinus histopathological examination was done. Results. IPL hair removal procedure was performed on 30 patients with their ages ranging from 16 to 41 years, with a mean (SD) of 23.1 (6.2) years. In this study 13 patients were presented with acute and 6 patients were presented with chronic phase. 11 patients had a positive history of one surgical treatment and presented recurrences. The overall recurrence rate after IPL treatment in this study was seen in 4 (13.3%) patients. The histopathological examination of our study showed that the hair fragments create a foreign body type granulomatous inflammatory reaction. This process could be triggering factor of the disease. Conclusions. IPL hair removal in affected area could be an alternative treatment to surgery or a choice treatment post surgery to decrease recurrence rate (Adv Clin Exp Med 2014, 23, 2, 277-282).
Objective: Gastric cancer is one of the most common types of cancers, which will result in irreparable harm in the case of misdiagnosis or late diagnosis. The purpose of this study is to investigate the capability of data mining techniques and disease risk factor characteristics to predict and diagnose the gastric cancer. Methods: In this retrospective descriptive-analytic study, we selected 405 samples from two groups of patient and healthy participants. A total of 11 characteristics and risk factors were examined. we used four Machine learning methods, Include support vector machine (SVM), decision tree (DT), naive Bayesian model, and k nearest neighborhood (KNN) to classify the patients with gastric cancer. The evaluation criteria to investigate the model on the database of patients with gastric cancer included Recall, Precision, F-score, and Accuracy. Data was analyzed using MATLAB® software, version 3.2 (Mathworks Inc., Natick, MA, USA). Results: Based on the results achieved from the evaluation of four methods, the accuracy rates of SVM, DT, naive Bayesian model, and KNN algorithms were 90.08, 87.89, 87.60, and 87.60 percent, respectively. The findings showed that the highest level of F-Score was related to the SVM (91.99); whereas, the lowest rate was associated with the KNN algorithm (87.17). Conclusion: According to the findings, the SVM algorithm showed the best results in classification of Test samples. So, this intelligent system can be used as a physician assistant in medical education hospitals, where the diagnosis processes are performed by medical students.
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