Ali Akbar Kiaei

This paper identifies optimal drug combinations for tongue neoplasms using a Graph Neural Network within the RAIN protocol, finding Cisplatin, Bleomycin, and Fluorouracil as effective treatments.

This paper introduces the AI-Enhanced RAIN protocol to optimize drug combinations for rectal neoplasms using GraphSAGE, systematic reviews, and meta-analysis, finding effective combinations with significant p-values.

The paper proposes a method using graph neural networks to recommend drug combinations for lung adenocarcinoma by targeting genes and proteins, finding Gefitinib, Paclitaxel, and Icotinib as the most effective combination.

This paper proposes a drug combination for Melanoma treatment using machine learning on genes and proteins, showing a 74-fold increase in effectiveness compared to single drugs.

This study uses machine learning to identify drug combinations that improve Tecovirimat efficacy for Monkeypox, showing significant reductions in p-values for treatment scenarios.

This paper uses reinforcement learning to recommend drug combinations targeting genes/proteins involved in stroke, showing improved efficacy and reduced p-values in network meta-analysis.