Global health experts annually face the crucial decision of selecting influenza strains for the next seasonal vaccine, a process complicated by the virus’s constant mutations. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has created VaxSeer, an AI tool designed to predict dominant flu strains and identify optimal vaccine candidates months in advance. Utilizing deep learning models trained on historical viral sequences, VaxSeer significantly enhances vaccine selection accuracy. The tool includes two prediction engines: one assessing viral spread and the other gauging vaccine effectiveness. In a 10-year retrospective study, VaxSeer’s predictions outperformed WHO recommendations in 90% of cases for the A/H3N2 strain. Beyond influenza, VaxSeer’s predictive capabilities could be extended to track the evolution of antibiotic-resistant bacteria and drug-resistant cancers, offering a transformative approach to public health interventions. This innovative model represents a significant advancement in staying ahead of rapidly evolving viruses.
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