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PubMed1978

Medical logic.

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History, 18th Century↗
PubMed1979

Medical logic.

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Education, Medical↗
PubMed1985

Logical and conceptual problems of existential psychiatry.

The author has argued that existential psychology and psychiatry are not consistent with existential philosophy, from which they derive their basic concepts. Existential philosophy treats consciousness as an epistemic and ontological absolute while existential psychology and psychiatry acknowledge the existence of unconscious mental processes. It is not possible to base a viable concept of psychodynamic psychotherapy, the nature of transference, or the efficacy of interpretation upon the radical concept of freedom, which is basic to existential philosophy. If psychiatrists wish to experiment with nonpsychoanalytic dynamic psychologies, then it is the author's opinion that the advancement of knowledge would be better served either by using existentialist concepts and principles consistently or by explicitly altering them in clearly defined ways for stated reasons, or by formulating psychodynamic hypotheses that do not lay claim to any foundation in existential philosophy.

Adult↗
PubMed2004

Fuzzy logic detection of medically serious suicide attempt records in major psychiatric disorders.

Clinical prediction of suicide is a complicated task. The focus for improved suicide risk detection is on the subgroup of individuals whose high suicide risk remains unrecognized by clinicians. We sought to evaluate the accuracy of Fuzzy Adaptive Learning Control Network (FALCON) neural networks, a nonlinear algorithm, in identification of this subgroup. The study sample included the Computerized Scale for risk of Suicide, including 21 suicide risk factors (including the target variable) drawn from 987 patient records, completed by staff clinicians during face-to-face interviews of hospitalized patients. FALCON evaluated all records in two steps: a) 612 for training and 375 for validation, and b) 887 for training and 100 for validation. The existence of previous medically serious suicide attempts (MSSAs) was chosen as the target variable because it is generally recognized as the strongest suicide risk factor. Sensitivity, specificity, and unknown answers among MSSA and non-MSSA were as follows: 612/375 FALCON, 91%, 85%, 11%, 15%; 887/100 FALCON, 94%, 82%, 20%, 14.5%, respectively. Trained FALCON, a nonlinear neural network, achieves respectable accuracy in detecting MSSA patients based on 20 suicide risk factors. Trained FALCON may therefore assist in identification of subgroup of individuals who remain unrecognized by clinicians and contribute to prevention of suicide.

Adolescent↗