Nature

Compact convolutional transformer for subject-independent motor imagery EEG-based BCIs

Motor imagery electroencephalography (EEG) analysis is crucial for the development of effective brain-computer interfaces (BCIs), yet it presents considerable challenges due to the complexity of the ...
Nature

Integrating convolutional and transformer networks for precise diagnosis of watershed and hemorrhagic stroke

According to C. Tsao, et al., 2023, and Hou, Shuai, et al., 2021, stroke is the second most frequent cause of death globally, characterized by its devastating impact on brain health. During a stroke, ...
ascopubs.org

SmokeBERT: A Bidirectional Encoder Representations From Transformers–Based Model for Quantitative Smoking History Extraction From Clinical Narratives to Improve Lung Cancer ...

We cross-validated four pretrained Bidirectional Encoder Representations from Transformers (BERT)–based models—BERT, BioBERT, ClinicalBERT, and MedBERT—by fine-tuning them on 90% of 3,261 sentences ...
Tech Times

Google Gemma 4 12B Brings Multimodal AI to 16GB Laptops, Free Under Apache 2.0

Google Gemma 4 12B, released June 3, is an open-weight multimodal model that processes text, images, audio, and video in a ...

Encoder-Free AI explained: The architecture behind Google’s Gemma 4 12B

A vast majority of multi-modal AI systems function as a relay race. For example, an image will come in through the Vision ...