Large language models (LLMs) are a rapidly evolving class of artificial intelligence with significant potential in clinical healthcare. Despite accelerating adoption, rigorous systematic evidence on clinical utility, patient safety, and implementation feasibility remains fragmented. To systematically review LLM applications across clinical domains, evaluate performance with appropriate contextual caveats, characterize implementation barriers, and identify ethical and regulatory considerations. Scientific databases were searched from January 2020 to January 2025. Studies evaluating transformer-based LLMs (≥10M parameters) in clinical settings were eligible. Data were independently double-extracted; quality was assessed using QUADAS-2, RE-A

Around 65 million individuals suffer from epilepsy worldwide, and when it is not properly treated, it is linked to higher rates of physical harm and mortality. Due to the requirement for long‐term therapy and the side effects of many medications, medication compliance is a significant issue. The purpose of this review was to summarize the findings of previous studies examining the quality of life (QOL), adherence, patient education, and medication knowledge, as well as the impact of a pharmacist‐led educational intervention. Additionally, to find out if these studies benefit epileptic patients, to find the appropriate method used to help them in all aspects of their lives, and to use these in future studies. A systematic and comprehensi

BSTRACT: BACKGROUND: Acne vulgaris(AV)is chronic inflammatory disease of pilosebaceous unit of young people. Patients with acne with or with out scarring might differ in regard to their immunological background from those free from acne. OBJECTIVES: To evaluate the problem of facial AV especially patients with scarring and to determine the frequency of associated skin diseases and to be compared with acne free control. METHODS: A cross sectional randomized controlled epidemiological study was conducted from Oct.2005-Oct. 2006.Three hundred students from Basra University; 132 (44%) males and 168 (56%) females were enrolled, their ages ranged from 18-25 (20.9±1.8) years. They were divided into: Group A those free from acne (98 individuals),G

S Khalifa E, AH Khalil I, N Adil A, AB Razan A…, 2009

     The current study was conducted to investigate Annona fruit pulp effects on the levels of various physiological biomarkers linked with insulin-dependent diabetes mellitus after disease induction in mice, as well as indications of oxidative stress and male hormones. The rats were separated into four groups, three of which were given Alloxan (90 mg/kg body weight) to induce diabetes, while the fourth served as a negative control. The first group of diabetic mice received no therapy, the second received metformin (600 mg/kg body weight) and the third received Annona fruit puree. The mice were sacrificed at the end of the experiment, to acquire blood and tissue samples from the liver, kidneys and spleen. The first untreated gro

The manganese doped zinc sulfide nanoparticles were synthesized by simple aqueous chemical reaction of manganese chloride, zinc acetate and thioacitamide in aqueous solution. Thioglycolic acid is used as capping agent for controlling the nanoparticle size. The main advantage of the ZnS:Mn nanoparticles of diameter ~ 2.73 nm is that the sample is prepared by using non-toxic precursors in a cost effective and eco-friendly way. The structural, morphological and chemical composition of the nanoparticles have been investigated by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) with energy dispersion spectroscopy (EDS) and Fourier transform infrared (FTIR) spectroscopy. The nanosize of the prepared nanoparticles was elucidated by Scan

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa