Biography:

Ms. Farasat Veisi is a researcher in Molecular Genetics at the Payame Noor University of Tehran Qeshm International Campus, Iran, specializing in the integration of artificial intelligence (AI) in biomedical research. Her work focuses on disease classification and prediction through machine learning and deep learning algorithms, aiming to enhance diagnostic accuracy and personalized treatment strategies. Her research explores AI-driven predictive modeling in healthcare, with notable contributions including:
• Advanced Predictive Healthcare Through Novel Deep Learning Models Using the Genetic Disorders Dataset
• AI-Driven Framework for Chronic Disease Prediction and Management
• Enhancing Breast Cancer Detection: FT-Transformer vs. Traditional Models
Farasat actively participates in international conferences, presenting her findings on the intersection of genetics, AI, and precision medicine. Her expertise spans bioinformatics, statistical modeling, and deep learning architectures such as CNNs, RNNs, and transformer models. Proficient in Python, R, and MATLAB, she applies advanced computational techniques to genomic data analysis and disease risk assessment. Her work is driven by a commitment to bridging genomics and AI, contributing to innovative solutions.