Biomedical engineering is undergoing a transformation due to AI and cloud computing, which are allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. This work examines these two computing paradigms in biomedical engineering, highlighting practical applications and new directions.
Biomedical engineering is undergoing a transformation due to AI and cloud computing, which are allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. This work examines these two computing paradigms in biomedical engineering, highlighting practical applications and new directions.
Dr. Madhusudhan H S an associate professor in the Department of Computer Science and Engineering at Vidyavardhaka College of Engineering, Mysuru, India. Dr. Punit Gupta is an associate professor in the department of Computer and Communication Engineering at Manipal University Jaipur, India. Dr. Pradeep Singh Rawat is an assistant professor with the Department of Computer Science and Engineering at DIT University, Dehradun, India. Dr. Dinesh Kumar Saini is a full professor at the School of Computing and Information Technology, Manipal University
Inhaltsangabe
1. Artificial Intelligence and Computational Biology in Drug Discovery 2. Techniques of AI/ML for Genomics Visualisation in Plants 3. Computing Architectures on the Cloud to Address Current Problems in Structural Bioinformatics 4. Application of AI for Diseases Detection and Prevention 5. AI for Diseases Detection and Prevention 6. Machine Learning Techniques for Detecting Lung Cancer 7. A Review on AI Approaches for the Detection of Diabetic Retinopathy 8. Intelligent Applications for Medical Image Analysis 9. Machine Learning Integration with Biomedical Problems 10. Intelligent Tools and Techniques for Real Life Diseases 11. Free Space Detection in Medical Image Analysis for the Visually Impaired Using Histogram Equalization and Adaptive Region Growing
1. Artificial Intelligence and Computational Biology in Drug Discovery 2. Techniques of AI/ML for Genomics Visualisation in Plants 3. Computing Architectures on the Cloud to Address Current Problems in Structural Bioinformatics 4. Application of AI for Diseases Detection and Prevention 5. AI for Diseases Detection and Prevention 6. Machine Learning Techniques for Detecting Lung Cancer 7. A Review on AI Approaches for the Detection of Diabetic Retinopathy 8. Intelligent Applications for Medical Image Analysis 9. Machine Learning Integration with Biomedical Problems 10. Intelligent Tools and Techniques for Real Life Diseases 11. Free Space Detection in Medical Image Analysis for the Visually Impaired Using Histogram Equalization and Adaptive Region Growing
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