Enhanced heart disease risk prediction using adaptive botox optimization based deep long-term recurrent convolutional network.

BackgroundHeart disease is the leading cause of death worldwide and predicting it is a complex task requiring extensive expertise. Recent advancements in IoT-based illness prediction have enabled accurate classification using sensor data.ObjectiveThis research introduces a methodology for heart disease classification, integrating advanced data preprocessing, feature selection, and deep learning (DL) techniques tailored for IoT sensor data.

Artificial Intelligence Based Customer Churn Prediction Model for Business Markets.

The introduction of artificial intelligence (AI) and machine learning (ML) technologies in recent years has resulted in improved company performance. Customer churn forecast is a difficult problem in many corporate sectors, particularly the telecommunications industry. Because customer churns have a direct impact on a company's total revenue, telecommunications firms have begun to develop 76 models to reduce churns at an earlier stage.

Metaheuristics with Deep Transfer Learning Enabled Detection and classification model for industrial waste management.

Rapid industrialization has led to the generation of a considerable amount of waste, both solid and liquid, in industrial fields like food processing, sugar, pulp, sago or starch, dairies, paper, fruit processing, poultry, distilleries, slaughterhouses, tanneries, and so forth. Despite the requirement for pollution control measures, the waste is discharged into water bodies or generally dumped on land without appropriate management, and thus becomes a significant source of environmental pollution and health hazards. The most essential step of waste management is the segregation of waste into the various elements, and normally this process is done automatically by hand-picking.

Pigeon Inspired Optimization with Encryption Based Secure Medical Image Management System.

Presently, technological advancements in the healthcare sector pose a challenging problem relevant to the security and privacy of health-related applications. Medical images can be considered significant and sensitive data in the medical informatics system. In order to transmit medical images in an open medium, the design of secure encryption algorithms becomes essential.

Deep Learning-Based Privacy-Preserving Data Transmission Scheme for Clustered IIoT Environment.

The Industrial Internet of Things (IIoT) has received significant attention from several leading industries like agriculture, mining, transport, energy, and healthcare. IIoT acts as a vital part of Industry 4.0 that mainly employs machine learning (ML) to investigate the interconnection and massive quantity of the IIoT data.