The Neuropsychiatric Approach to the Assessment of Patients in Neurology
Bibliographic record
Abstract
Neuropsychiatry is a clinical neuroscience specialty focused on the evaluation and treatment of patients who present with symptoms at the intersection of neurology and psychiatry. Neuropsychiatrists assess and manage the cognitive, affective, behavioral, and perceptual manifestations of disorders of the central nervous system. Although fellowship training in behavioral neurology-neuropsychiatry exists in the United States and several other countries internationally, the need for neuropsychiatric expertise greatly outweighs the number of specialists in practice or training. This article serves as a primer for both neurologists and psychiatrists seeking to improve or refresh their knowledge of the neuropsychiatric assessment, including detailing aspects of the history-taking, physical exam, psychometric testing, and associated diagnostic work-up. In doing so, we urge the next generation of neurologists and psychiatrists to take on both the opportunity and challenge to work at the intersection of both clinical neuroscience specialties using an integrated neuropsychiatric perspective.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".