AI cancer tools may rely on 'shortcut learning' rather than genuine biological signals

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...
IEEE

Supervised Machine Learning for Brain Tumor Progression Prediction on Limited and Imbalanced Data: An Exploratory Study

Abstract: Accurately predicting glioma progression remains a significant clinical challenge due to the disease's heterogeneity, unpredictable progression patterns, and the limitations of imaging-based ...

Developing personalized vaccines for cancer via machine learning

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...
IEEE

Brain Tumor Detection and Classification Using LSTM

Abstract: Brain tumor detection and classification play a crucial role in medical imaging, where timely and accurate diagnosis can significantly impact patient health. This study proposes an approach ...