Artificial Intelligence and Its Applications

This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence and its Applications, ICAIA 2023, held in Pune, India, during December 1819, 2023.

The 37 full papers and 3 short papers presented in these two volumes were carefully reviewed and selected from 217 submissions. The conference focused on three primary domains: Use of AI in Health Care; Machine Vision and Image Processing; Automated and Digital Manufacturing Systems.

Inhalt

.- Artificial Intelligence in the Healthcare Sector: Possibilities and Problems.

.- A Study on revolution of healthcare industry with transformational Artificial Intelligence tool.

.- The Hybrid Cardiac Risk Assessment and Prediction Model Using Convolutional Neural Network.

.- Deep Learning Applications for Malaria Detection and Diagnosis: A Review.

.- Environmental Considerations in the Ethics of AI Adoption in Healthcare: Striving for Sustainable and Responsible Practices.

.- Harnessing the Power of Cognitive Computing: Assessing Point-of-Care Decision Support Tools in Oncology Practice.

.- Critical Analysis in Use of AI in Health Care Management.

.- Classification and Prediction of Spinal Tuberculosis Disease using Optimization of Convolution Neural Network using Spatial and Temporal Constraints.

.- Artificial Intelligence for Remote Healthcare in Underserved Areas: Enhancing Access and Quality of Healthcare Delivery.

.- Machine learning based Skin cancer detection and recognitions techniques in IoT environment.

.- Validation of a chronic kidney disease prediction system using machine learning techniques.

.- Real-Time Feedback Detection using Emotion Detection and Facial Recognition.

.- Revolutionizing Vision Tasks: Unlocking Potential through Patch-based Approaches.

.- Automated Knee Implant Identification from 2D Templates using Image Processing and Artificial Intelligence- An Experimental Approach.

.- Crop Analysis and Classification based on Phenotype using Ensemble Learning.

.- Classification & identification with health benefit assessment and nutrient profile of brewed tea utilizing computer vision with ML & DL and sensory approaches.

.- Enhancing Industrial Automation Flexibility through Neural Network-Empowered Machine Vision Applications.