The future of AutoML in histology looks promising, with advancements in deep learning and neural networks paving the way for more sophisticated and accurate models. As computational power continues to increase and data becomes more abundant, the potential for AutoML to revolutionize histological analysis and diagnostics will only grow. Moreover, ongoing research and collaboration between data scientists and medical professionals will further enhance the capabilities and applications of AutoML in histology.
