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Showing 2 results for Yaghoobi Notash
Routine Para Clinic Evaluation Of Preoperative Patients: A New Solution For An Old Problem
A Yaghoobi Notash , S.sh Fatemi ,
Volume 63, Issue 3 (12 2005)
Abstract

Background: Routine Para clinic evaluation of preoperative patients tends to cause unnecessary costs, extra risk to the patients, inefficient operating room schedules and extra medico legal risk. Furthermore, it seldom affects clinician's preoperative evaluation and decision making process for healthy patients. Numerous studies have shown that about 60% of these will not be performed if they are ordered according to recognizable indications based on history and physical examinations unfortunately the ‘indication based’ method can not replace to “routine” method due to difficulty and complexity to performing.

Materials and Methods: We reviewed records of 1700 patients on a retrospective descriptive study in Sina Hospital from September 2000 to the end of September 2001. These patients had undergone general surgical procedures and were categorized as American society of anesthesiologists classification I or II. Results of complete blood count, fasting blood sugar, blood urea nitrogen, serum creatinin, sodium, potassium, chest X-ray, electrocardiogram and urinalysis were compared between patients under 40 years of age (n= 894) and patients aged 40 and over (n= 806).

Results: Among 4935 tests performed in patients under 40 years of age, only 1004 (20.3%) were indicated, and treatment plan was not altered due to the results of routine tests in any case. In the other group, patients aged 40 and over, 6300 tests were performed, from which 3361 (53.3%) were indicated and treatment plans of 5 patients were influenced by the results of routine tests.

Conclusion: Routine preoperative Para clinical tests is not cost effective method, otherwise the “indication based” also is difficult and complex method. We offer routine preoperative Para clinical tests only in patients over 40 years to combine ease of “routine” with a great reduction in medical costs and no adverse affect to patient care.


The prediction of lymphedema via the combination of the selected data mining algorithms
Anaram Yaghoobi Notash , Peiman Bayat, Shahpar Haghighat, Ali Yaghoobi Notash ,
Volume 79, Issue 11 (February 2022)
Abstract
Background: Breast cancer is the second leading cause of cancer death in women, after lung cancer. Due to the importance of predicting this disease, the use of data mining methods in medical research is more significant than before. Data mining algorithms can be a great help in preventing the development of lymphedema in patients. The aim Of this study was to create a diagnosis system that can predict the probability of lymphedema in breast cancer patients.
Methods: In the present study, the factors of lymphedema in 1117 patients with breast cancer have been collected. The likelihood of developing lymphedema is predicted using ensemble learning via 5 heterogeneous classification algorithms, feature selection and the genetic algorithm (The Two-layer Ensemble Feature Selection method). After collecting the data of patients with breast cancer from 2009 to 2018, and data preprocessing using the optimized ensemble learning algorithm and feature selection, we will examine the likelihood of developing lymphedema for the new patient. Finally, the factors affecting the disease have been extracted. Excluding the time of collecting statistical data, the period of the study was from September 2019 to February 2021. This study is performed at Seyed Khandan Rehabilitation Center, Tehran, Iran.
Results: The results of algorithms showed that the accuracy of the ensemble learning method with selected classification algorithms (SVM with RBF kernel) is 87% and the accuracy of the ensemble learning with feature selection method is 90%. According to the final evaluation of the proposed method, the most effective risk factors for lymphedema have been extracted.
Conclusion: Unfortunately, treatment and diagnosis are not without complications, and one of the most important of these complications in breast cancer is lymphedema in the upper extremities, which can affect the quality of life in patients. It is essential to have a method that can accurately suggest to a specialist whether a new patient will develop lymphedema in the future or how likely it is to develop it, using patient’s own clinical and demographic characteristics.
 

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