Complete Graphical Language for Hermiticity-Preserving Superoperators

Universal and complete graphical languages have been successfully designed for pure state quantum mechanics, corresponding to linear maps between Hilbert spaces, and mixed states quantum mechanics, corresponding to completely positive superoperators. In this paper, we go one step further and present a universal and complete graphical language for Hermiticity-preserving superoperators. Such a language opens the possibility of diagrammatic compositional investigations of antilinear transformations featured in various physical situations, such as the Choi-Jamiolkowski isomorphism, spin-flip, or entanglement witnesses. Our construction relies on an extension of the ZW-calculus exhibiting a normal form for Hermitian matrices

Simultaneous bilateral optic neuropathy and myelitis revealing paraneoplastic neurological syndrome associated with multiple onconeuronal antibodies.

Paraneoplastic neurological syndromes (PNS) are immune-mediated complications of cancer associated with a broad spectrum of clinical manifestations. Optic neuropathy (ON) and myelitis are frequent manifestations of multiple sclerosis and neuromyelitis optic spectrum disorders but are considered as non-classical in PNS. Here, we report a case of PNS revealed by simultaneous bilateral ON and myelitis related to a cluster of three neural autoantibodies, in the setting of small cell lung cancer

Neura: a specialized large language model solution in neurology

Large language models’ (LLM) ability in natural language processing holds promise for diverse applications, yet their deployment in fields such as neurology faces domain-specific challenges. Hence, we introduce Neura: a scalable, explainable solution to specialize LLM. Blindly evaluated on a select set of five complex clinical cases compared to a cohort of 13 neurologists, Neura achieved normalized scores of 86.17% overall, 85% for differential diagnoses, and 88.24% for final diagnoses (55.11%, 46.15%, and 70.93% for neurologists) with rapid response times of 28.8 and 19 seconds (9 minutes and 37.2 seconds and 8 minutes and 51 seconds for neurologists) while consistently providing relevant, accurately cited information. These findings support the emerging role of LLM-driven applications to articulate human-acquired and integrated data with a vast corpus of knowledge, augmenting human experiential reasoning for clinical and research purposes