International Journal of Intelligent Systems and Applications in Engineering

A Hybrid Deep Learning Approach for Predicting Patient Health Outcomes in Mobile Healthcare Applications

Akhil Tirumalasetty — 2026-02-14

Along with mobile health care apps, deep learning has transformed health monitoring and prediction. A hybrid approach based on deep learning for mobile health systems for precise patient health outcome prediction is proposed in this paper. It exploits Convolutional Neural Networks (CNN) to extract the features followed by Long Short Term Memory (LSTM) networks to learn from the sequential pattern for efficient analysis of the patients' vitals, past medical history and real-time sensor data. Also Attention Mechanism plays very significant role in highlighting important health parameters thus interprets and explains levels of data which helps in decision improvement through the model. We train the hybrid model on heterogeneous healthcare data and test it with accuracy, precision, recall and F1-score. The experimental results demonstrate significant benefits in terms of predictive consistency and real-time flexibility than traditional deep learning models. This framework could change the base of mobile healthcare applications to initiate early disease detection, personal treatment recommendations, and timely involvement in the patient journey that would facilitate healthier and more effective healthcare.

Efficient Large-Scale Data based on Big Data Framework using Critical Influences on Financial Landscape

Bhanu Prakash Paruchuri — 2026-02-14

One of the most recent commercial and technological concerns in the technological era is big data. Hundreds of millions of events occur on an ongoing basis. The financial sector is significantly involved in the computation of big data events. As a result, hundreds of millions of financial transactions occur in the financial industry each day. Financial practitioners and analysts perceive it as an emerging challenge in the data administration and analytics of a variety of financial products and services. In addition, financial services and products are significantly affected by big data. Determining the financial concerns that big data significantly affects is, thus, an important topic to research with the impacts. This paper used these concepts to show the current state of finance and how big data affects financial markets, institutions, internet finance, financial management, internet credit service companies, fraud detection, risk analysis, financial application management, and more. The connection between big data and economic aspects can be better understood by doing an exploratory literature review of secondary data sources. Because big data in finance is a relatively new concept, further research directions will be proposed at the end of this study.