Advancements in Deep Learning for Predicting Organic Molecular Spectra and Diagnosing Active Pulmonary Tuberculosis
Researchers have developed a deep learning model called DetaNet for predicting selected organic molecular spectra. The model utilizes a combination of atomic and electronic features, as well as spherical harmonic functions, to generate accurate predictions. The researchers used publicly available datasets, including optimized structures and various properties of molecules, to train and validate the model. The DetaNet model and trained parameters are available for reference, along with the program used for spectrum prediction. This research contributes to the growing field of deep learning in spectroscopy and has potential applications in various scientific disciplines.