SCIHYPO - A Deep Learning Framework for Data-Driven Scientific Hypothesis Generation from Extensive Literature Analysis

Scientific progress relies heavily on hypothesis generation, yet conventional methods often rely on expert intuition, limiting exploration of new ideas. To address this, we introduce SciHypo, a deep learning framework leveraging scientific literature to generate fresh hypotheses across diverse fields. SciHypo employs advanced natural language processing, including Generative Pre-trained Transformer to analyze patterns, relationships, and gaps in research. This allows the model to uncover latent connections and propose novel research trajectories. Filter search algorithms ensure the production of relevant hypotheses. A key strength is SciHypo's adaptability across scientific disciplines, enabling transdisciplinary hypothesis generation. Results demonstrate its ability to propose hypotheses resonating with experts, advancing scientific frontiers.