Evaluation of Bayesian belief networks for diagnosis of psychotic disorders

The thesis examined the inter-rater reliability and procedural validity of four computerised Bayesian belief networks (BBNs) which were developed to assist with the diagnosis of psychotic disorders. The results of this research indicated that BBNs can significantly improve diagnostic reliability and may represent an important advance over current diagnostic methods. The professional portfolio investigated, through the presentation of case studies and review of literature relevant to each case study, how comorbidity and context of depression may impact on cognitive behavioural therapy treatment.

Mining condensed sets of frequent episodes with more accurate frequencies from complex sequences

Many previous approaches to frequent episode discovery only accept simple sequences. Although a recent approach has been able to nd frequent episodes from complex sequences, the discovered sets are neither condensed nor accurate. This paper investigates the discovery of condensed sets of frequent episodes from complex sequences. We adopt a novel anti-monotonic frequency measure based on non-redundant occurrences, and dene a condensed set, nDaCF (the set of non-derivable approximately closed frequent episodes) within a given maximal error bound of support. We then introduce a series of effective pruning strategies, and develop a method, nDaCF-Miner, for discovering nDaCF sets. Experimental results show that, when the error bound is somewhat high, the discovered nDaCF sets are two orders of magnitude smaller than complete sets, and nDaCF-miner is more efficient than previous mining approaches. In addition, the nDaCF sets are more accurate than the sets found by previous approaches.

An efficient one-pass method for discovering bases of recently frequent episodes over online data streams

The knowledge embedded in an online data stream is likely to change over time due to the dynamic evolution of the stream. Consequently, infrequent episode mining over an online stream, frequent episodes should be adaptively extracted from recently generated stream segments instead of the whole stream. However, almost all existing frequent episode mining approaches find episodes frequently occurring over the whole sequence. This paper proposes and investigates a new problem: online mining of recently frequent episodes over data streams. In order to meet strict requirements of stream mining such as one-scan, adaptive result update and instant result return, we choose a novel frequency metric and define a highly condensed set called the base of recently frequent episodes. We then introduce a one-pass method for mining bases of recently frequent episodes. Experimental results show that the proposed method is capable of finding bases of recently frequent episodes quickly and adaptively. The proposed method outperforms the previous approaches with the advantages of one-pass, instant result update and return, more condensed resulting sets and less space usage.

Melatonin : an overlooked factor in schizophrenia and in the inhibition of anti-psychotic side effects

This paper reviews melatonin as an overlooked factor in the developmental etiology and maintenance of schizophrenia; the neuroimmune and oxidative pathophysiology of schizophrenia; specific symptoms in schizophrenia, including sleep disturbance; circadian rhythms; and side effects of antipsychotics, including tardive dyskinesia and metabolic syndrome. Electronic databases, i.e. PUBMED, Scopus and Google Scholar were used as sources for this review using keywords: schizophrenia, psychosis, tardive dyskinesia, antipsychotics, metabolic syndrome, drug side effects and melatonin. Articles were selected on the basis of relevance to the etiology, course and treatment of schizophrenia. Melatonin levels and melatonin circadian rhythm are significantly decreased in schizophrenic patients. The adjunctive use of melatonin in schizophrenia may augment the efficacy of antipsychotics through its anti-inflammatory and antioxidative effects. Further, melatonin would be expected to improve sleep disorders in schizophrenia and side effects of anti-psychotics, such as tardive dyskinesia, metaboilic syndrome and hypertension. It is proposed that melatonin also impacts on the tryptophan catabolic pathway via its effect on stress response and cortisol secretion, thereby impacting on cortex associated cognition, amygdala associated affect and striatal motivational processing. The secretion of melatonin is decreased in schizophrenia, contributing to its etiology, pathophysiology and management. Melatonin is likely to have impacts on the metabolic side effects of anti-psychotics that contribute to subsequent decreases in life-expectancy.