We describe our work on HEPAR II, a probabilistic causal model for diagnosis of liver disorders. The model, a Bayesian network capturing the causal interactions among various risk factors, diseases, symptoms, and test results, is based on expert knowledge combined with clinical data captured in medical records. The main applications of HEPAR II are assistance is diagnosis and training of beginn...

In this paper, we examine whether Bayesian networks are sensitive to precision of their parameters in the context of Hepar II, a sizeable Bayesian network model for diagnosis of liver disorders. Rather than entering noise into probability distributions, which was done in prior studies, we change their precision, starting with the original values and rounding them systematically to progressively...

The theory of belief networks offers a relatively new approach for dealing with uncertain information in knowledge-based (expert) systems. In contrast with the heuristic techniques for reasoning with uncertainty employed in many rule-based expert systems, the theory of belief networks is mathematically sound, based on techniques from probability theory. It therefore seems attractive to convert ...

Metode: Penelitian in vitro ini menggunakan kultur sel kanker kolon manusia (Caco-2), sel kanker hepar manusia (HepG2), sel kanker payudara tergantung hormon (MCF7) dan kultur sel normal hepar manusia (Chang Liver). Efek sitotoksik diukur melalui uji MTT melalui penentuan kadar yang membunuh 50% sel (IC50). Mekanisme sitotoksik dipelajari dengan menentukan pengaruh penambahan γ-sitosterol pada ...

Endoplasmic reticulum (ER) stress is emerging as an important modulator of different pathological process and as a mechanism contributing to homocysteine (Hcy)-induced hepar injury. However, the molecular event that Hcy-induced ER stress in the hepar under the atherosclerosis background is currently unknown. Endoplasmic reticulum oxidoreductin 1α (ERO1α) plays a crucial role in maintaining ER s...

OBJECTIVES To evaluate the effect of the anthroposophic drug hepar magnesium D10 intravenously administered on seasonal fatigue symptoms. DESIGN Time series with two measurements per week, starting before onset of treatment until three measurements after finishing treatment in a regular way. SETTINGS Six anthroposophic general practitioner practices in the Netherlands. SUBJECTS Twenty-thr...

The Hepar II system is based on a Bayesian network model of a subset of the domain of hepatology in which the structure of the network is elicited from an expert diagnostician and the parameters are learned from a database of medical cases. The model follows the assumption made in the database that each patient case is diagnosed with a single disorder, i.e., disorders are mutually exclusive. In...

In this paper, we examine the influence of overconfidence in parameter specification on the performance of a Bayesian network model in the context of Hepar II, a sizeable Bayesian network model for diagnosis of liver disorders. We enter noise in the parameters in such a way that the resulting distributions become biased toward extreme probabilities. We believe that this offers a systematic way ...

While most knowledge engineers believe that the quality of results obtained by means of Bayesian networks is not too sensitive to imprecision in probabilities, this remains a conjecture with only modest empirical support. We summarize the results of several previously presented experiments involving Hepar II model, in which we manipulated the quality of the model’s numerical parameters and chec...