diagnoslik

Diagnoslik is a concept used in medical informatics to denote a structured representation of diagnostic hypotheses and their supporting evidence, including estimated likelihoods and recommended actions. It is not a universally standardized term but appears in some literature and software contexts.

The term combines "diagnosis" with a suffix used in several European languages to convey similarity or likelihood; its etymology is informal and context-dependent.

A diagnoslik record typically lists multiple hypotheses with fields such as label, observed signs, tests, prior probability, posterior probability, and suggested next steps.

Representations commonly rely on probabilistic reasoning (Bayesian networks, likelihood ratios) or rule-based scoring; systems update probabilities as new data arrive, enabling dynamic revision.

Use cases include differential diagnosis support, triage in emergency settings, remote or point-of-care decision support, and training tools for clinicians.

Benefits include structured reasoning, documentation of uncertainty, and reproducibility; limitations involve data quality, model opacity, potential bias, and the risk of overreliance.

Example: a patient with fever and cough may have diagnoslik entries for influenza, COVID-19, and bacterial pneumonia, with initial priors; PCR tests or imaging update post-test probabilities and guide actions.

See also: differential diagnosis, Bayesian reasoning, decision support systems.