Investigation of Disease Prediction Based on DNA Using Deep Model Techniques
Abstract
Precision medicine has never had more prospects thanks to the explosive growth of genetic data caused by the quick development of genomic sequencing technologies. This paper investigates the use of sophisticated deep neural networks (DNNs) for risk factor evaluation and illness prediction using DNA sequences. The suggested method uses extensive genomic datasets to create reliable prediction models that can recognize intricate genetic patterns linked to a range of illnesses. The technology captures both spatial and sequential dependencies in DNA data by integrating recurrent neural networks (RNNs) with convolutional neural networks (CNNs).
Fields of Study & Subjects
Machine Learning in Bioinformatics
Fractal and DNA sequence analysis
Genetic Associations and Epidemiology
Publication details
- Journal / source
- Advances in computational intelligence and robotics book series
- Pages
- 225–240
- Publication date
- 25 February 2026
- Language
- EN
- Document type
- Book chapter