Artificial Intelligence Medical Compendium

Major depressive disorder (MDD) is highly recurrent, and psychosocial stress is a central precipitant of relapses. Daily choices require weighing potential rewards against costs, a process disrupted in MDD that may contribute to relapse. Here, we tes... read more 

Neuroscience aims to uncover the algorithms by which the brain builds and manipulates rich internal representations of objects, agents, and places. Existing reverse-engineering frameworks remain ineffective for identifying these algorithms. Here, we ... read more 

One of the goals of ecological biogeography is to accurately predict where major vegetation types, such as forests or grasslands, can establish themselves. Alas, our current understanding of the mechanisms by which environmental variables jointly inf... read more 

Recent advances in brain decoding work has shown the potential of Vision Transformers (ViTs) to learn mappings from neural representation to visual features. Here we present CortexDecoder, a brain decoding framework mapping fMRI flatmaps to images vi... read more 

Protein immunogenicity is a major cause of biologic drug failure, leading to the production of anti-drug antibodies (ADA) that accelerate drug clearance, rejection of repeated doses, abolished efficacy, and sometimes life threatening anaphylaxis in p... read more 

Functional genomics in crops increasingly depends on integrating information from an extensive literature and heterogeneous multi-omics datasets. Large language models (LLMs) offer a powerful approach to synthesizing these resources and revealing hid... read more 

Machine learning models for molecular discovery often train on bioactivity data from heterogeneous assays, yet assay context is rarely explicitly represented. We investigate whether natural-language assay descriptions provide predictive information b... read more 

What does biological wiring actually contribute to neural computation? Behavioral experiments can test whether a model produces the right outputs, but they cannot determine whether its internal representations are biologically faithful. Brunton et al... read more 

Ammonium (NH4 +) pollution in wastewater poses severe ecological and health risks. This study introduces a magnetic biochar composite (SB@MFO) synthesized from sugarcane bagasse and MnFe2O4 for efficient NH4 + removal. The composite exhibits a mesopo... read more 

Maple syrup quality evaluation involves multiple parameters, including color classification, flavor assessment, and the measurement of sugar concentration, which are influenced by the complex chemical composition of the syrup matrix. Conventional qua... read more