Diagnosis articles from across Nature Portfolio

We developed a medical large language model with 176 billion parameters and fine-tuned it to learn physicians’ inferential diagnosis. We showed that the model accurately diagnoses common and rare diseases across specialties, aligns with medical standards, and can be integrated into clinical workflows to effectively enhance physician diagnostic performance.

Training a model on fetal and paediatric magnetic resonance images with synthesized artefacts enhances the model’s generalization across downstream tasks and patient populations.

Cardiovascular diseases require precise and continuous monitoring, but current PPG technology is limited to single-point sensing. Here, the authors present a display with organic photodiodes that enables multi-point PPG, high-resolution imaging, and user-interactive sensing.

We developed a medical large language model with 176 billion parameters and fine-tuned it to learn physicians’ inferential diagnosis. We showed that the model accurately diagnoses common and rare diseases across specialties, aligns with medical standards, and can be integrated into clinical workflows to effectively enhance physician diagnostic performance.

Artificial intelligence (AI) is increasingly permeating the fabric of medicine, but getting full benefits will likely require fundamental changes in practice. Accepting this will be challenging for many clinicians. However, it may be necessary to ensure that AI’s ambitious promises translate into real-life improvement.

Training a model on fetal and paediatric magnetic resonance images with synthesized artefacts enhances the model’s generalization across downstream tasks and patient populations.