The problem of medical waste over the past tow decades has emerged as one of the most important issues.

Which have negative effects on health and the environment ,and as a result specialists looked into the field.

Public health and research issues . This phenomenon in all its dimensions and efforts made For their containment through the development of health and environmental controls for the disposal of such wastes.

In a safe manner starting form the source of these wastes and the various health organizations are  finished The final treatment ,and this is why the producers of hazardous medical waste.        &nb

It is well- known that the distinguished scholastic journal is a crucial cornerstone, which contributes to the scientific integrity of a particular academic institution. The establishment of the Al-Kindy College of Medicine (AKCM), University of Baghdad, in 1998 urged the need to issue Al-Kindy College Medical Journal (KCMJ).

To know the effect of bio-enhancer (zeolite), biohealth, mineral fertilizers and their interactions, the possibility of replacing mineral fertilizers with bio-enhancers and bio-enhancers, and their effect on some potato yield measurements. A field experiment was conducted at one of the field stations of the College of Agricultural Engineering Sciences, University of Baghdad, near the electronic calculator center, research station (F) in Al-Jadriya region in the loam mixture soil during autumn season 2021-2022 AD, It was designed using a completely randomized block design (RCBD) with three replicates. The factors of the study experiment included three levels of zeolite (0, 6 tons ha-1, and 12 tons ha-1), which were symbolized by (Z0)

The influence of different thickness (500, 1000, 1500, and 2000) nm on the electrical conductivity and Hall effect measurements have been investigated on the films of copper indium gallium selenide CuIn1-xGaxSe2 (CIGS) for x= 0.6.The films were produced using thermal evaporation technique on glass substrates at R.T from (CIGS) alloy. The electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated and calculated as function of thickness. All films contain two types of transport mechanisms of free carriers, and increases films thickness was fond to increase the electrical cAnductivity whereas the activation energy (Ea) would vary with films thickness. Hall Effect analysis resu

The main goal of this work is to obtain the plasma electron temperature Te by optical emission spectroscopy of low pressure microwave argon plasma, as a function of working pressure and microwave power. A plasma system was designed and constructed in our laboratory using a magnetron of domestic microwave oven with power 800W without any commercial part. The applied voltage on the magnetron electrical circuit is changed for the purpose of obtaining the variable values of the microwave power. The spectral detection is performed with a spectrometer of wavelength range (200−1000nm). The working pressure and magnetron applied voltage were 0.3-3.0mbar and 180-240V, respectively. Two methods had been applied to estimate the electron temperatu

The right of the patient to know the medical risks surrounding the medical intervention is one of the most prominent rights based on the principle of "physical safety", which has undergone several stages of development until it reached the development of the patient's independence in making medical decision without relying on the doctor, The patient's prior informed consent is informed of his / her medical condition. We will study this development in accordance with the French March 4, 2002 legislation on the rights of patients in the health system, whether it was earlier and later. We will highlight the development of the patient's right to "know the medical risks surrounding medical intervention" The legislation and its comparison with th

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a