Benjamin Victor Ineichen

This paper uses NLP to analyze 500,000 animal drug studies and links them to clinical data, finding that only 3.1% reach regulatory approval and that species diversity and blinding improve translation success.

This scoping review summarizes the use of large language models in biomedical NLP tasks, highlighting their growing application in text classification, relation extraction, and named entity recognition.

This study investigates the clinical relevance of dilated Virchow-Robin spaces (VRS) as an imaging biomarker in multiple sclerosis, finding they correlate with vascular pathology rather than immune cell accumulation.

This study shows that in vivo MRI can detect remyelination in a nonhuman primate model of MS with high accuracy, suggesting its potential for preclinical and clinical applications.

Auto-STEED automates extraction of experimental parameters and risk of bias items from in vivo publications, achieving high accuracy and significant time savings.

This study conducts a systematic review and meta-analysis of leptomeningeal enhancement (LME) in multiple sclerosis and other neurological diseases, finding its association with clinical and imaging features in MS.

The paper shows that axonal mitochondria diameter correlates with surrounding myelin thickness across species and CNS tracts, providing a measurable indicator for remyelination in experimental models.