From the 1 of 6 linked papers with an AI index.
6 papers
Institutional Equity Holdings Prediction Using Node Affinities of Dynamic Graphs
Emad Izadifar, Zahed Rahmati
The paper introduces a benchmark for predicting institutional equity holdings by modeling portfolio weights as node affinity predictions on a temporal bipartite graph of managers a…
Enhancing Graph Neural Networks Using Proximity Graphs for Dust Source Emission Forecasting
Maryam Sanisales, Zahed Rahmati, Ali Darvishi Boloorani +1
Accurate prediction of dust source emissions is critical for mitigating the significant environmental and health hazards posed by dust storms. Traditional forecasting methods often…
Semantic Reasoning in Medicine: The Role of Knowledge Graphs Across Five Key Domains
Haniye Sherafatmandjoo, Mohammad Akbari, Zahed Rahmati
Knowledge graphs (KGs) have emerged as a promising solution for integrating and reasoning over complex biomedical and clinical data in healthcare. By representing structured relati…
Where Black-box Drug-Target Interaction Prediction Models Look: Cross-Method Explainability
Ali Vefghi, Zahed Rahmati, Mohammad Akbari
Drug-target interaction (DTI) and affinity (DTA) predictors increasingly achieve strong benchmark scores, yet their internal use of sequence, fingerprint, and graph features often…
Drug-Target Interaction/Affinity Prediction: Deep Learning Models and Advances Review
Ali Vefghi, Zahed Rahmati, Mohammad Akbari
Drug discovery remains a slow and expensive process that involves many steps, from detecting the target structure to obtaining approval from the Food and Drug Administration (FDA),…
Relational Graph Convolutional Networks for Sentiment Analysis
Asal Khosravi, Zahed Rahmati, Ali Vefghi
With the growth of textual data across online platforms, sentiment analysis has become crucial for extracting insights from user-generated content. While traditional approaches and…