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It was dark, the moon shone bright, the green meadow was covered in snow, when a carriage sped by lightning-fast, slowly turning the corner. Inside, people were standing seated, deep in silent conversation, when a shot rabbit went ice-skating on the sandy bank. And a blond-haired young man with coal-black hair sat on a green box, which was painted red. Next to him, an old spinster, barely sixteen years old, held a butter roll in her hand, which was smeared with lard. #poetry
Good Morning and Merry Christmas ! #nostr
Another unfortunate clinical trial failure for a CNS indication (Parkinson). All primary and secondary endpoints were missed: #science #parkinson #neurodegeneration #brain
This is really interesting: https://www.nature.com/articles/s41562-024-02046-9 "Large language models surpass human experts in predicting neuroscience results" A study on how well trained LLMs can predict the "correctness" of a new neuroscience study/claim based on looking into the associations of the mentioned claims/words in the new study compared to a reference set of thousands of previously published neuroscience papers. The idea here is that there are associations hidden in the vast amount of literature out there that humans in general and singular scientists in particular just cannot read, remember, grasp and comprehend anymore due to the exponential growth in studies. Importantly all thus trained LLMs outperform a large panel of human expert in predicting whether or not a new study or a fake study is true. This is really fascinating and could have major implications to identify new disease MoA hypothesis, target validationa nd dicovery, discover hidden connections and low-hanging treatment option fruits that nobody has yet considered or simply just weed out fake or irrelevant new er publications. #ai #science #neuroscience #drugs #future #LLM #nostr
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