AI and Machine Learning in Urology: Current Uses and Future Directions | Chapter 8 | Science and Technology: Developments and Applications Vol. 8

Background: Artificial Intelligence (AI) and Machine Learning (ML) have significantly transformed modern urology by enhancing diagnostic accuracy, surgical precision, and patient management. AI-driven innovations are increasingly integrated into urological practice, enabling early disease detection, predictive analytics, risk stratification, and robotic-assisted surgeries. This paper explores the current landscape of AI in urology, analyzing its applications in diagnostics, treatment planning, and surgical interventions. It highlights AI-driven technologies' benefits, challenges, and future research directions in optimizing patient care.

 

Methods: A comprehensive literature review was conducted on AI applications in urology, examining studies on machine learning models—including deep learning and reinforcement learning—for detecting prostate, kidney, and bladder cancer, predictive analytics for disease progression, and AI-enhanced robotic surgeries. The analysis encompasses regulatory considerations, ethical implications (including data bias and patient privacy concerns), and real-world applications of AI in clinical settings.

 

Results: AI performs superiorly in diagnostic imaging, histopathological analysis, and personalized treatment recommendations. Machine learning models enhance risk stratification, enabling more targeted therapeutic approaches. AI-driven robotic surgical systems enhance precision and reduce complications, while AI-powered remote monitoring tools optimize postoperative care. However, data bias, interpretability, regulatory constraints, and ethical concerns hinder widespread adoption.

 

Conclusion: AI is revolutionizing urology by improving efficiency, accuracy, and patient outcomes. Future advancements in AI-driven precision medicine, autonomous robotic surgery, and AI-integrated telemedicine are promising. Addressing challenges related to data privacy, bias mitigation, and regulatory approval will be crucial for the seamless integration of AI into urological practice. Continued research and interdisciplinary collaboration will enhance AI's role in transforming urological healthcare.

 

Author (s) Details

Aadhitya Sriram
Department of Computer Science and Engineering, College of Engineering, Guindy Anna University, Chennai, Tamil Nadu -600025, India.

 

Shreenidhi Sriram
Meta via PwC, Seattle, USA.

 

Kalpana Ramachandran
Department of Anatomy, Sri Ramachandra Institute of Higher Education & Research (SRIHER), Chennai, Tamil Nadu, PIN: 600116, India.

 

Sriram Krishnamoorthy
Department of Urology & Renal Transplantation, Sri Ramachandra Institute of Higher Education & Research (SRIHER), Chennai, Tamil Nadu, PIN: 600116, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v8/5018

Case Studies: The Impact of Artificial Intelligence on STEM Education | Chapter 10 | An Overview of Literature, Language and Education Research Vol. 10

Artificial intelligence can improve the quality of teaching and learning in education. It can have a more positive impact by serving as a new special purpose “method of intervention” that can change our curriculum in education. Artificial intelligence refers to technology that reacts to its environment and responds to tasks in a way that optimizes the levels of success. In this chapter, we certain tasks which were carried out by educational robotics and learning management systems that could maximize the success of teaching and learning, specifically in Mathematics and computer science education, were discussed. The two types of technology discussed in this chapter are robotics and a learning management system. We These two types of technology were considered in a general setting and examples of actual usage in classroom situations were provided. The authors present for each type, an example of intervention of artificial intelligence. In the case of robotics, research was carried out with preservice computer science teachers (n =75). These teachers were asked about their experiences when utilizing robotics when learning computer programming. Kolb’s Experiential Learning Cycle guided that study. In the section that follows, we potentials of robotics in STEM Education were surveyed. In the case of using the learning management systems, a mixed-mode research study was carried out with science students in one study and then with engineering students (n =162) learning mathematics. It was found that there is ample potential for the use of artificial intelligence in education to enhance teaching to support more effective individualized learning. We in this chapter, the benefits of using educational robotics and learning management systems for teaching and learning in education with pre-service teachers and engineering students were shown.

 

Author (s) Details

 

Deonarain Brijlall
Department of Mathematics, Durban University of Technology, South Africa.

 

F Abakah
Department of Mathematics, Durban University of Technology, South Africa.

 

A Saxena
Dev Sanskriti Vishvavidyalaya University, Uttarakhand, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/aoller/v10/4389

A Review on Nanotechnology and Nanorobotics: A Miraculous And emerging Tool in Nanomedicine | Chapter 5 | Advanced Concepts in Pharmaceutical Research Vol. 6

Nanotechnology, is the combination of recently developed scientific technology and modified engineering that focuses on production, design and application of a system at an atomic or molecular level. It helps in creating machines or robots by theoretical engineering near about nanometer scale is called “Nanorobotics”. These are named like ‘nanorobots’, ‘nanoids’, ‘nanites/nanomites’ ‘Industrial robots’, ‘humanoid’, ‘surgical robots’ etc. In this article focused on concept, types, working, pharmaceutical approaches, design, advantages, disadvantages, application and future aspects through robotic projects on nanomedicine delivering agent nanorobots in different fields. The development of design of nanorobots has been done by using various approaches such as: Biochip, Nubots, Positional Nano assembly, Usage of Bacteria etc. These are implemented by using several components such as sensors, actuators, control, power, communication and by interfacing cross- special scales between organic inorganic systems. Due to specific site operation mechanism leads no any harmful activities and no side effects in applications. The initial cost of design development is high but accurate delivery of medicine to target site is the boon to mankind. These nano devices are used for the purpose of maintaining and protecting the human body against pathogens in different areas (food, industry, agriculture, farming, space technology etc.). It is helpful in the treatment of cancer (In Obese Prostate Cancer, colon cancer, Kidney cancer etc.), cerebral Aneurysm, removal of kidney stones, Gene therapy, Nano dentistry, Neurosurgery, Diagnosis and Testing, Diamond nanotechnology for skin treatments, implementation of Anti–HIV etc. Various new developed pharmaceutical science-based nanotechnology in various fields of biotechnology, biomaterials synthesis, drug delivery, in diagnosis and treatment monitoring using medical imaging, etc. showed great potential in the field of Nanomedicine. The use of nanorobotic with nanotechnology could become the boon to mankind and a miraculous emerging tool in future nano era.

Author(s) Details:

Gita Chaurasia,
Siddhant College of Pharmacy, Pune, Maharashtra, India.

Please see the link here: https://stm.bookpi.org/ACPR-V6/article/view/13415

A Hybrid Approach to Support Robotic Polishing Process Planning | Chapter 11 | Research and Developments in Engineering Research Vol. 8

 Currently, machinelike polishing and manual labour are used to complete the finishing stages of the produce of moulds. This stage of the procedure is not only ultimate expensive, but it is likewise currently experience a shortage of knowledgeable people. The production industry has anticipated towards robotic electronics to assist the polishing process in order to address these questions and serve the fuller needs of Industry 4.0. One factor that needs expected considered when automating the polishing process is the order of machined physiognomy that need to be treated. The research presented in this place examines the preparation and optimisation of the polishing process for the production of moulds and is a component of a more considerable project that aims to automate 80% of the existent human process. This chapter names an optimisation technique for done or made by machine polishing process sequencing that aims to simultaneously placate polishing sequence tests and minimize polishing period. A hybrid approach joining both hereditary algorithms and analytical hierarchic processes is proposed established the specific traits of polishing process sequencing. A multi-objective fitness function is delineated using AHP, containing the calculation of polishing occasion and the evaluation of polishing process rules. The projected process sequencing has been favorably demonstrated on test piece instances.

Author(s) Details:

K. Wang,
Bristol Robotics Laboratory (BRL), School of Engineering, University of the West of England, Cold Harbour Lane Bristol, United Kingdom.

L. Ding,
Bristol Robotics Laboratory (BRL), School of Engineering, University of the West of England, Cold Harbour Lane Bristol, United Kingdom.

F. Dailami,
Bristol Robotics Laboratory (BRL), School of Engineering, University of the West of England, Cold Harbour Lane Bristol, United Kingdom.

J. Matthews,
Bristol Robotics Laboratory (BRL), School of Engineering, University of the West of England, Cold Harbour Lane Bristol, United Kingdom.

Please see the link here: https://stm.bookpi.org/RADER-V8/article/view/11981

Neurorehabilitation in Neuro-COVID| Book Publisher International

 Corona-virus disease 2019 (COVID-19), caused by the newly emerged coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)], affected the public health in the world. Acute and chronic neurological issues, considered as consequences of COVID-19, are denominated Neuro-COVID.

 

Physical rehabilitation should be offered to all patients with Neuro-COVID.

 

Rehabilitation procedures begin during the acute stage and continue after hospital discharge – in post-acute phase and during long-term treatment.

 

We present principles of neurorehabilitation (NR) in neuro-COVID.

 

Special attention was paid to the process of NR of patients with some neurological complications of COVID-19, as follows: cerebral vascular accidents, spinal ischemic stroke, relapses of multiple sclerosis, Guillain-Barre syndrome, development of rare diseases (as cerebellar ataxia or amyotrophic lateral sclerosis /motor neuron disease/), etc. The importance of grasp and gait recovery for patients’ autonomy in everyday life is underlined.

 

We emphasize on the impact of Information and Communication technologies (ICT) in the clinical practice: robotics, neurorobotics, virtual reality.

 

We accentuate on the role of digital competences of members of the interdisciplinary and multi-professional rehabilitation team.

 

We present typical and rare clinical cases (consequences and complications of COVID-19), treated by robotic neurorehabilitation.

 

Our results demonstrated positive effects of ICT-application on the neuroplasticity, functional recovery and quality of life of neurological patients.

Author(s) Details:

Ivet Borissova Koleva,
Medical University of Sofia, Bulgaria, Multi-profile Hospital for Long-term Care and Rehabilitation “Serdika” with Medical Center for Robotic Neurorehabilitation “ReGo”, Bulgaria and National Heart Hospital, Cardiorehabilitation Department, Sofia, Bulgaria.

Borislav Radoslavov Yoshinov,
Medical Faculty, Sofia University, Sofia, Bulgaria.

Radoslav Radoslavov Yoshinov

University for Library Studies and Information Technologies UNIBIT, Sofia, Bulgaria.

Please see the link here: https://stm.bookpi.org/NNC/article/view/11103 

Refurbishing Recent Emerging Technology Trends in Construction Industry| Chapter 10 | Techniques and Innovation in Engineering Research Vol. 6

 Adoption of current digital revolution technology is necessary today to speed up trade and serves as the foundation for building improvement. Incorporating and undertaking of the technologies in the way that cloud-based communication and cooperation solution, BIM, Construction Management (CM) Software, AR/ VR, 3D publication, Digital Twins, AI, Big Data, IoT, Blockchain, Modular Construction, Offsite Manufacturing, Prefabrication, Robotic, Drones, Mobile Apps and 5G expedite the progress in Construction Industry (CI). The objective concerning this article search out provide the climbing pattern amongst digital electronics trends in explanation which are recognized based on a study completed activity during 2020-2022. Result discloses that number of construction technology currents vary from 4 to 20 for CI, and ultimately reaches to 27 for Civil Engineering (CE). Adoption and implementation of these science trends increases effectiveness and productivity, reduces risks and time, supports higher freedom and green sustainability, and improves the overall commerce. The challenges and solutions are very embracing engaged of construction. Thus, the CI is constantly developing with preliminary of new technologies and these creative technologies show potential in change construction manufacturing operations and provides directions for future projects.

Author(s) Details:

Gayatri Mahajan,
Department of Architecture, Allana College of Architecture, Pune (Maharashtra), India.

Please see the link here: https://stm.bookpi.org/TAIER-V6/article/view/8956

Study on Millennium Robotics, Powered by Artificial Intelligence and Cloud Engineering | Chapter 11 | New Approaches in Engineering Research Vol. 10

 With the industrial revolution in the early twentieth century, humans began a new era of automation of things and activities that were previously done manually, such as repetitive manufacturing processes, sewing machines, painting, and more. Humans were the smartest species on the planet, and they were effective in leading these endeavours. Success, on the other hand, is accompanied by unbounded optimism for the future, the age of Artificial Intelligence, which will far transcend human capabilities. From the human brain project and Artificial Intelligence to industrial and self-aware robots, this research paper will touch on these technologies. From autonomous cars to aeroplanes to smart cities to traffic lights, technology has not looked back, merging Artificial Intelligence (AI) with robotic automated systems that have advanced quickly from supporting humans to completely replacing humans, and have also become self-aware. Solar panels power factories, and if everything is working properly, it can predict a problem on the horizon and modify or recover accordingly. Elon Musk says, "The fraction of intelligence that is not human is increasing, and we humans will eventually represent a very small percentage of intelligence."

Author (S) Details

Khaled Elbehiery
DeVry University, USA.

Hussam Elbehiery
Vanridge University, USA.

View Book :- https://stm.bookpi.org/NAER-V10/article/view/2987

Design of a Waste Compacting Robot for Residential Use: An Advanced Study | Chapter 10 | New Approaches in Engineering Research Vol. 10

 There are various robots on the market now that can help with a variety of domestic activities. The goal of this research is to create a garbage compactor robot that can be used in urban areas. Soda cans were picked as the rubbish kind. It was feasible to specify the components of robot systems for compacting, locomotion, and electronic/control, as well as model and simulate them, with the current work. In this approach, garbage compactor robots will allow garbage to arrive semi-processed in the treatment plant; a single collecting waste vehicle will be able to cover a broader area; street cleaners will be able to work in other sections of the city; and landfills will be easier to treat.

Author (S) Details

Bruno Seixas Gomes de Almeida
Mechanical Engineering Department, Mechanical Engineering, Federal University of Rio de Janeiro – UFRJ, Brazil.

Ivan Barbosa Couto Neto
Mechanical Engineering Department, Mechanical Engineering, Federal University of Rio de Janeiro – UFRJ, Brazil.

Armando Carlos de Pina Filho
Urban Engineering Program, Mechanical Engineering, Federal University of Rio de Janeiro – UFRJ, Brazil.

View Book :- https://stm.bookpi.org/NAER-V10/article/view/2986