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

Bashar bin cold language poetic in critical discourse
Modern Literary

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In this study, the behavior of screw piles models with continuous helix was studied by conducting laboratory experimental tests on a single screw pile that has several aspect ratios (L/D) under the influence of static axial compression loads. The screw piles were inserted in a soft soil that has a unit weight of 18.72 kN/m3 and moisture content of 30.19%. Also, the soil has a liquid limit of 55% and a plasticity index of 32%. A physical laboratory model was designed to investigate the ultimate compression capacity of the screw pile and measure the generated porewater pressure during the loading process. The bedding soil was prepared according to the field unit weight and moisture content and the failure load was assumed correspondin

This research presents and discuss the results of experimental investigation carried out on geogrids model to study the behavior of geogrid in the loose sandy soil. The effect of location eccentricity, depth of first layer of reinforcement, vertical spacing, number and type of reinforcement layers have been investigated. The results indicated that the percentage of bearing improvement a bout (22 %) at number of reinforced layers N=1 and about (47.5%) at number of reinforced layers N=2 for different Eccentricity values when depth ratio and vertical spacing between layers are (0.5B and 0.75B) respectively

Existence of these soils, sometimes with high gypsum content, caused difficult problems to the buildings and strategic projects due to dissolution and leaching of gypsum by the action of waterflow through soil mass. In this research, a new technique is adopted to investigate the performance of replacement and geosynthetic reinforcement materials to improve the gypseous soil behavior through experimential set up manufactured loaclally specially for this work. A series of tests were carried out using steel container (600*600*500) mm. A square footing (100*100) mm was placed at the center of the top surface of the bed soil. The results showed that the most effective thickness for the dune sand layer with geotextile at the interface, within

The numerical analysis was conducted to studying the influence of length to diameter ratio (L/D) on the behavior of the soil treated with sand columns treated with 8% sodium silicate for both floating and end bearing type by using finite element method (Plaxis 3D Foundation ) for isolated foundation of real dimensions. The analysis’s study indicate that in the floating type the best improvement ratio was achieved at (L/D=8) when using columns with a diameter of (0.5, 0.7), but when using columns with a diameter of 0.3 m, it was noticed that the bearing improvement ratio increases with increasing (L/d). While the results of the analysis for end bearing type show that the higher improvement ratio was achieved at (L/D=4) when using columns w