Monis Luqman Mohammed

Papers

Total Citations

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About

Monis Luqman Mohammed is a researcher at the forefront of intelligent robotic systems in dentistry and healthcare. His primary research focuses on integrating guided local search models, continuous time neural networks, and robotic assistance to enhance the precision and safety of surgical procedures. Mohammed’s most cited work, "Improving the Efficiency of Dental Implantation Process Using Guided Local Search Models and Continuous Time Neural Networks With Robotic Assistance" (2020, 17 citations), addresses one of dentistry’s most challenging issues: the dental implant replacement process. By leveraging advanced computational models and robotics, he demonstrates how automated systems can track oral hygiene and perform complex surgeries with greater accuracy and reduced risk. This contribution is particularly notable for its potential to transform quality control and safety measures in dental surgery. Mohammed’s research bridges the gap between artificial intelligence and clinical practice, offering practical solutions that improve patient outcomes. His work stands as a significant step toward the broader adoption of robotics in medicine, making him a key voice in the future of automated surgical assistance.