Exponential distribution is one of most common distributions in studies and scientific researches with wide application in the fields of reliability, engineering and in analyzing survival function therefore the researcher has carried on extended studies in the characteristics of this distribution.

In this research, estimation of survival function for truncated exponential distribution in the maximum likelihood  methods and Bayes first and second method, least square method and Jackknife dependent in the first place on the maximum likelihood method, then on Bayes first method then comparing then using simulation, thus to accomplish this task, different size samples have been adopted by the searcher us

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

     In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates  sample size , and it replicates  for the real value for parameters, for reliability times values  we take .

Results were compared by using mean square error (MSE), the result appears as follows :

The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

The aim of this study is to assess the prevalence of lung infections among a group of hospitalized cancer patients who received chemotherapy as well as to describe a population of these patients. The clinical data and demographic information were collected from the archived files of  in-patients  referred to  hematology center  / Baghdad Teaching Hospital / Medical City , ministry of health, Iraq  during the period  of  2018.

    This study was carried out on 250 patients with different types of cancer ,they were mostly of age group (40 - 49)  59 / 250 (23.6)% , (14-19) 49 /250 (19.6%) and (60-69) 41/ 250(16.4%) . The patients had two major types of hematological malignancies

In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using   is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.

Background: Lung cancer is responsible for the most
cancer deaths in both men and women throughout the
world. Deaths from lung cancer (160,440 in 2004,
according to the National Cancer Institute) exceed the
number of deaths from four other major cancers combined
(breast, colon, pancreatic and prostate).
Objective: To assess the behavior and the approaches of
lung cancer in a sample of Iraqi patients.
Methods: This descriptive retrospective study was
performed using the records of 390 patients proved to have
lung cancer that had attending the Thoracic Surgery
Department of Surgical Specialties Hospital-Medical City
\Baghdad for the period from January, 1st
, 2001 to
December, 31st
,2002.
Res

Background: The diagnosis of interstitial lung disease (ILD) is frequently delayed, because clinical clues are neglected and respiratory symptoms are ascribed to more common pulmonary diagnosis such as asthma and chronic obstructive pulmonary disease in the primary care setting.
Objective: To evaluate the diagnostic yield of open lung biopsy in patients with suspected ILD in relation to clinical and radiological features.
Patients and methods: Thirty-five patients were admitted with suspected interstitial lung disease (ILD), and scheduled for open lung biopsy (OLB) in Ghazi AL-Hariri hospital for surgical specialty, were included in this study. Data collected from the patient's files (who were subjected to open lung biopsies which

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone