Madiha Javeed
Papers
1
Total Citations
60
H-Index
1
About
Madiha Javeed is a leading researcher in sustainable healthcare technologies, specializing in the intersection of deep learning, pattern recognition, and physical health monitoring. Her work focuses on developing intelligent systems that can analyze daily life-log routines to detect complications in elderly individuals, aiming to prevent injuries and reduce costly recovery stages. Her most-cited paper, "HF-SPHR: Hybrid Features for Sustainable Physical Healthcare Pattern Recognition Using Deep Belief Networks" (2021, 60 citations), introduces a novel hybrid feature extraction approach combined with deep belief networks to accurately identify physical healthcare patterns from complex, real-world data. This contribution is pivotal in enabling proactive, non-invasive health monitoring for aging populations. Beyond this, Javeed’s research advances the use of sustainable AI frameworks that minimize computational overhead while maximizing predictive accuracy, making her work highly relevant for deployment in resource-constrained settings. Her achievements demonstrate a clear commitment to translating machine learning innovations into practical tools that improve quality of life, and her growing citation impact underscores her influence in the fields of healthcare informatics and ambient assisted living.
Research Focus
Key Achievements
Top Papers
- 1