The Concept of Medical Treatment and Guidelines for Physicians in Islamic Perspective

In fact, good health is the ultimate end of medicine for everyone through medical treatment. Islam does approve necessary measures to sustain good health. Thus its sustenance senses the subjects to avoid undue pains and sufferings. For this purpose medications and medical treatment is measured as a recognized tool in Islamic law. Therefore, this research paper reveals that numerous Muslim scientists worked on different branches of science,  and hence the Muslim physicians execute one of the most complicated “eye surgery” almost six hundred (600) years earlier than the European physicians. Indeed, it is the Muslim scientists who discovered the ‘force of gravity’, ‘blood circulation’, ‘laws of motion’. Factually, they developed the ‘theory of evolution’, ‘differential and integral mathematics’ and many more in the field of science. Consequently, the words of Campbell in this regard are very important to note that: “the European medical system is Arabian not only in origin but also in its structure”, which signify that “Muslim scientists are directly responsible for the European renaissance”. Resultantly, this paper argues that ‘medical treatment is an obligation if one’s life is in danger’ since preservation and protection of life is one of the primary objectives of Shariah. Although, in extraordinary circumstances, seeking medical treatment is highly encouraged in Islam, and an ill person is supposed to pursue medical treatment because Allah almighty has made both the illness and the cure.

Bayesian Approach to the Mixture Models

This thesis deals with Bayesian inference of mixture densities using censored data. Type-I and type-II mixtures are considered that belong to two or one parameter exponential family. Selection of distribution is made keeping in view the novelty and applicability. These include Inverse Weibull, Pareto type-II, shifted exponential distribution and lastly mixture of Burr type XII and Rayleigh distributions that belong to type-II mixture model. These mixture distributions have not been explored so far in Bayesian setup. Bayes estimators for the parameters of the mixture models are derived in closed forms using type-I right censoring. To conduct Bayesian analysis, Informative (Gamma and Squared Raylegh) priors and non-informative (Uniform and Jeffreys) priors are considered while three loss functions, Squared Error Loss Function, Weighted loss function and Quadratic loss function are employed. A wide simulation study is made to scrutinize the properties of proposed Bayes estimators. Parameters of the mixture model are also tested through hypothesis testing procedure for inverse Weibull and Pareto type- II models. For the inverse Weibull mixture model when all parameters are unknown Bayes estimators can not be obtained in closed forms thus Gibbs sampling and Importance sampling techniques are used to obtain Bayes estimates in this case. Bayesian predictive density is used to obtain Bayes predictive intervals and reliability estimator. Predictive intervals for one and two sample prediction are also obtained that help to predict failure times of future observations. Bayes estimators using limiting form are also derived. Though type-I right censoring is considered throughout the dissertation, however, shifted exponential distribution is also explored through progressive censoring scheme. For the said case, Bayes estimators, credible intervals, Expected test termination time which is considered very useful for life testing experiments, are derived and evaluated. Applications of these mixtures are also presented by applying a real data set in each case.