Purpose. Prognostic assessments after acute brain injury are largely narrative, and how prognostic language relates to subsequent care has not been measured at scale. We quantified where it is written and its association with a subsequent code-status limitation. Materials and Methods. Multidatabase observational study...
A. Gorenshtein, Y. Adiniaev, A. Srour et al.· medRxiv· 0 citations
OBJECTIVE
To develop and validate an open-source evaluation framework that assesses clinical AI diagnostic systems across multiple clinically relevant dimensions (accuracy, cost, time, invasiveness, physician effort, and safety behaviors), addressing the limitations of accuracy-only benchmarks.
MATERIALS AND METHODS...
M. Sorka, A. Gorenshtein, H. Abramovitch et al.· JAMIA Journal of the America...· 0 citations
OpenEvidence (OE) is a retrieval-augmented clinical AI tool. We evaluated the references OE returned to 150 standardized prompts across five specialties, analyzing all 4979 citations. No reference was confirmed as fabricated; three abstracts had attribution errors. Most references were recent and high-impact, though jo...
Tami Lotan, Mahmud Omar, Y. Barash et al.· npj Health Systems· 0 citations
Large language models for medical consultation are often evaluated after a clinical problem has already been made clear, although real consultations may begin with a vague, minimized, or misframed concern. We evaluated three API models across four physician-authored, multi-turn vignettes under baseline and entry-to-car...
Yining Hua, C. Ayubcha, Hongbin Na et al.· 0 citations
No system was reliable across every axis tested: accuracy fell as competing papers were added, interpretation-requiring facts were harder than stated ones, two-paper synthesis was rarely achieved, and only some systems recognized absent evidence.
A. Gorenshtein, Tian-Yu Zhang, M. Westover et al.· medRxiv· 0 citations
It is suggested that sustained clinician engagement, rather than algorithmic accuracy, may be the key barrier to effective clinical AI use in emergency departments.
L. Leibovitch, Adi Ahituv, A. Gorenshtein et al.· Nature Medicine· 2 citations
Before AI-assisted triage enters rheumatology referral pathways, systems should separate objective clinical evidence from interpretive framing, and urgency and psychological attribution should be treated as auditable safety signals.
Mahmud Omar, M. Naffaa, R. Agbareia et al.· Rheumatology· 0 citations
Current evidence does not support the use of LLMs for diagnosis, treatment selection, or patient education in AD/MCI without clinician oversight, and are further limited by small heterogeneous evaluations, sparse hallucination measurement, and absence of prospective clinical validation.
Y. Adiniaev, Mahmud Omar, Oved Daniel et al.· Neurological Sciences· 0 citations
Under this benchmark, OpenEvidence produced fewer missed emergencies than the historical ChatGPT Health comparison, while errors concentrated in over-triage and evidence-seeking refusal.
Eric Jia, Mahmud Omar, Y. Barash et al.· International Journal of Med...· 0 citations
This retrospectively re-decoded 3,373 P300-speller selections from 47 people with amyotrophic lateral sclerosis, reconstructing a neural posterior and combining it with 25 language priors ranging from 5-grams to 46.7-billion-parameter models to reveal how strongly a fused brain-computer interface decision depends on it...
A. Gorenshtein, M. Omar, E. Jia et al.· medRxiv· 1 citation
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