> For IHM risk prediction, we utilized the LSTM model, CW-LSTM model, transformer, LR, AdaBoost, XGBoost, and random forest (RF) models. For 5-year BCS prediction, we used MLP, AdaBoost, XGBoost, and RF models.
All of those acronyms are obsolete machine learning techniques from prior to the current trend of large language models. In other words, this paper is not reporting that any actually-deployed AI is failing, it's reporting that a group of researchers tried to build an AI for evaluating health, but failed to do so.
The article links to another news article which links to http://dx.doi.org/10.1038/s43856-025-00775-0 which says:
> For IHM risk prediction, we utilized the LSTM model, CW-LSTM model, transformer, LR, AdaBoost, XGBoost, and random forest (RF) models. For 5-year BCS prediction, we used MLP, AdaBoost, XGBoost, and RF models.
All of those acronyms are obsolete machine learning techniques from prior to the current trend of large language models. In other words, this paper is not reporting that any actually-deployed AI is failing, it's reporting that a group of researchers tried to build an AI for evaluating health, but failed to do so.