Enhancing Minimally Invasive Surgery with Deep Learning-Based Medical Robotics
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Keywords

Medical Robotics
Surgical Efficiency
Surgical Robotics

How to Cite

[1]
Dr. Carlos Diaz, “Enhancing Minimally Invasive Surgery with Deep Learning-Based Medical Robotics: Utilizes deep learning algorithms to enhance the capabilities of medical robotics for performing precise and minimally invasive surgical procedures, improving patient outcomes and recovery times”, Journal of Bioinformatics and Artificial Intelligence, vol. 3, no. 2, pp. 253–262, Oct. 2023, Accessed: Nov. 12, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/106

Abstract

Minimally invasive surgery (MIS) has revolutionized the field of surgery by offering patients shorter recovery times, reduced pain, and fewer complications compared to traditional open surgeries. The advent of medical robotics has further advanced MIS by providing surgeons with enhanced precision and control during procedures. However, challenges such as complex anatomical structures and hand-eye coordination still exist. Deep learning, a subset of artificial intelligence, has emerged as a promising tool to address these challenges and improve the capabilities of medical robotics in MIS. This paper explores the application of deep learning algorithms in enhancing medical robotics for MIS, highlighting their potential to improve patient outcomes and revolutionize surgical practices.

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References

Prabhod, Kummaragunta Joel, and Asha Gadhiraju. "Artificial Intelligence for Predictive Analytics in Healthcare: Enhancing Patient Outcomes Through Data-Driven Insights." Journal of AI-Assisted Scientific Discovery 2.1 (2022): 233-281.

Pushadapu, Navajeevan. "The Importance of Remote Clinics and Telemedicine in Healthcare: Enhancing Access and Quality of Care through Technological Innovations." Asian Journal of Multidisciplinary Research & Review 1.2 (2020): 215-261.

Potla, Ravi Teja. "AI and Machine Learning for Enhancing Cybersecurity in Cloud-Based CRM Platforms." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 287-302.

Thatoi, Priyabrata, et al. "Natural Language Processing (NLP) in the Extraction of Clinical Information from Electronic Health Records (EHRs) for Cancer Prognosis." International Journal 10.4 (2023): 2676-2694.

Bao, Y.; Qiao, Y.; Choi, J.E.; Zhang, Y.; Mannan, R.; Cheng, C.; He, T.; Zheng, Y.; Yu, J.; Gondal, M.; et al. Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy. Proc. Natl. Acad. Sci. USA 2023, 120, e2314416120.

Krothapalli, Bhavani, Lavanya Shanmugam, and Jim Todd Sunder Singh. "Streamlining Operations: A Comparative Analysis of Enterprise Integration Strategies in the Insurance and Retail Industries." Journal of Science & Technology 2.3 (2021): 93-144.

Gayam, Swaroop Reddy. "Artificial Intelligence for Natural Language Processing: Techniques for Sentiment Analysis, Language Translation, and Conversational Agents." Journal of Artificial Intelligence Research and Applications 1.1 (2021): 175-216.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Compliance and Regulatory Reporting in Banking: Advanced Techniques, Models, and Real-World Applications." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 151-189.

Putha, Sudharshan. "AI-Driven Natural Language Processing for Voice-Activated Vehicle Control and Infotainment Systems." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 255-295.

Sahu, Mohit Kumar. "Machine Learning Algorithms for Personalized Financial Services and Customer Engagement: Techniques, Models, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 272-313.

Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Models for Risk-Based Pricing in Health Insurance: Techniques and Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 170-207.

Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Models for Predictive Analytics in Insurance: Techniques, Applications, and Real-World Case Studies." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 244-290.

Devan, Munivel, Bhavani Krothapalli, and Mahendher Govindasingh Krishnasingh. "Hybrid Cloud Data Integration in Retail and Insurance: Strategies for Seamless Interoperability." Journal of Artificial Intelligence Research 3.2 (2023): 103-145.

Kasaraneni, Ramana Kumar. "AI-Enhanced Pharmacoeconomics: Evaluating Cost-Effectiveness and Budget Impact of New Pharmaceuticals." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 291-327.

Pattyam, Sandeep Pushyamitra. "AI-Driven Data Science for Environmental Monitoring: Techniques for Data Collection, Analysis, and Predictive Modeling." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 132-169.

Kuna, Siva Sarana. "Reinforcement Learning for Optimizing Insurance Portfolio Management." African Journal of Artificial Intelligence and Sustainable Development 2.2 (2022): 289-334.

Prabhod, Kummaragunta Joel. "Integrating Large Language Models for Enhanced Clinical Decision Support Systems in Modern Healthcare." Journal of Machine Learning for Healthcare Decision Support 3.1 (2023): 18-62.

Pushadapu, Navajeevan. "Optimization of Resources in a Hospital System: Leveraging Data Analytics and Machine Learning for Efficient Resource Management." Journal of Science & Technology 1.1 (2020): 280-337.

Potla, Ravi Teja. "Integrating AI and IoT with Salesforce: A Framework for Digital Transformation in the Manufacturing Industry." Journal of Science & Technology 4.1 (2023): 125-135.

Gayam, Swaroop Reddy, Ramswaroop Reddy Yellu, and Praveen Thuniki. "Artificial Intelligence for Real-Time Predictive Analytics: Advanced Algorithms and Applications in Dynamic Data Environments." Distributed Learning and Broad Applications in Scientific Research 7 (2021): 18-37.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Customer Behavior Analysis in Insurance: Advanced Models, Techniques, and Real-World Applications." Journal of AI in Healthcare and Medicine 2.1 (2022): 227-263.

Putha, Sudharshan. "AI-Driven Personalization in E-Commerce: Enhancing Customer Experience and Sales through Advanced Data Analytics." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 225-271.

Sahu, Mohit Kumar. "Machine Learning for Personalized Insurance Products: Advanced Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 60-99.

Kasaraneni, Bhavani Prasad. "AI-Driven Approaches for Fraud Prevention in Health Insurance: Techniques, Models, and Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 136-180.

Kondapaka, Krishna Kanth. "Advanced Artificial Intelligence Techniques for Demand Forecasting in Retail Supply Chains: Models, Applications, and Real-World Case Studies." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 180-218.

Kasaraneni, Ramana Kumar. "AI-Enhanced Portfolio Optimization: Balancing Risk and Return with Machine Learning Models." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 219-265.

Pattyam, Sandeep Pushyamitra. "AI-Driven Financial Market Analysis: Advanced Techniques for Stock Price Prediction, Risk Management, and Automated Trading." African Journal of Artificial Intelligence and Sustainable Development 1.1 (2021): 100-135.

Kuna, Siva Sarana. "The Impact of AI on Actuarial Science in the Insurance Industry." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 451-493.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Dynamic Pricing in Insurance: Advanced Techniques, Models, and Real-World Application." Hong Kong Journal of AI and Medicine 4.1 (2024): 258-297.

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