Agricultural Resilience and Disaster Management for Sustainable Harvest -- Plant Disease Recognition using Machine Learning and Deep Learning Classifiers -- Securing Lives and Assets: IoT-Based Earthquake and Fire Detection for Real-Time Monitoring and Safety -- An Early Detection of Fall Using Knowledge Distillation Ensemble Prediction Using Classification -- Deep Learning Methods for Precise Sugarcane Disease Detection and Sustainable Crop Management -- An Interactive Interface for Plant Disease Prediction and Remedy Recommendation -- Tilapia Fish Freshness Detection using CNN Models -- Chilli Leaf Disease Detection using Deep Learning -- Damage Evaluation Following Natural Disasters Using Deep Learning -- Total Electron Content Forecasting in Low Latitude Regions of India: Machine & Deep Learning Synergy -- Disease and Abnormalities Detection using ML and IOT -- Early Phase Detection of Diabetes Mellitus Using Machine Learning -- Diabetes Risk Prediction through Fine-Tuned Gradient Boosting -- Early Detection of Diabetes using ML-based Classification Algorithms -- Prediction Of Abnormality Using IoT and Machine Learning -- Detection of Cardiovascular Diseases using Machine Learning Approach -- Mild Cognitive Impairment Diagnosis Using Neuropsychological Tests and Agile Machine Learning -- Heart Disease Diagnosis using Machine Learning Classifiers -- Comparative Evaluation of Feature Extraction Techniques in Chest X Ray Image with Different Classification Model -- Application of Deep Learning in Healthcare -- Transfer Learning Approach for Differentiating Parkinson's Syndromes using Voice Recordings -- Detection of Brain Tumor Type Based on FANET Segmentation and Hybrid Squeeze Excitation Network with KNN -- Mental Health Analysis using Rasa and Bert: Mindful -- Kidney Failure Identification using Augment Intelligence and IOT Based on Integrated Healthcare System -- Efficient Characterization of Cough Sounds Using Statistical Analysis -- An Efficient Method for Heart Failure Diagnosis -- Novel Machine Learning Algorithms for Predicting COVID-19 Clinical Outcomes with Gender Analysis -- A Genetic Algorithm-Enhanced Deep Neural Network for Efficient and Optimized Brain Tumor Detection -- Diabetes Prediction using Ensemble Learning -- Cancer Detection Using AI -- A Predictive Deep Learning Ensemble Based Approach for Advanced Cancer Classification -- Predictive Deep Learning: An Analysis of Inception V3, VGG16, and VGG19 Models for Breast Cancer Detection -- Innovation in the Field of Oncology: Early Lung Cancer Detection and Classification using AI -- Colon Cancer Nuclei Classification with Convolutional Neural Networks -- Genetic Algorithm-based Optimization of UNet for Breast Cancer Classification: A Lightweight and Efficient approach for IoT Devices -- Classification of Colorectal Cancer Tissue Utilizing Machine Learning Algorithms -- Prediction of Breast Cancer using Machine Learning Technique.

The two-volume set CCIS 2053 and 2054 constitutes the refereed post-conference proceedings of the 13th International Advanced Computing Conference, IACC 2023, held in Kolhapur, India, during December 15-16, 2023. The 66 full papers and 6 short papers presented in these proceedings were carefully reviewed and selected from 425 submissions. The papers are organized in the following topical sections: Volume I: The AI renaissance: a new era of human-machine collaboration; application of recurrent neural network in natural language processing, AI content detection and time series data analysis; unveiling the next frontier of AI advancement. Volume II: Agricultural resilience and disaster management for sustainable harvest; disease and abnormalities detection using ML and IOT; application of deep learning in healthcare; cancer detection using AI.