Can AI Improve Brain Tumor Diagnosis?

Spotting brain tumors in MRI scans can be tricky. Doctors rely on manual checks and sometimes help from computers, but these methods have their drawbacks. They might not work well on all scans due to the tumors' complex shapes and the need for precise analysis. Also, these systems can be slow and may not work well on new data. To fix these issues, researchers are trying something new. They've developed a model using a type of artificial intelligence called Xception convolutional neural network. This model is designed to learn from lots of data and adapt to new scans better. It has been improved with special techniques to prevent it from making wrong predictions. The key here is using a big dataset and fine-tuning the model for specific tasks. This helps the model recognize different types of brain tumors, like meningiomas, gliomas, and pituitary tumors, more accurately. When tested, this AI model performed impressively. It could correctly identify brain tumor types in scans 98. 039% of the time. It did particularly well for each type, with accuracy rates over 96%. This kind of AI could be a game-changer in hospitals. It could help doctors make more accurate diagnoses faster.