Abstract. Case-base administrators face a choice of many maintenance algorithms. It is well-known that these algorithms have different biases that cause them to perform inconsistently over different datasets. In this paper, we demonstrate some of the biases of the most commonly-used maintenance algorithms. This motivates our new approach: maintenance by a committee of experts (MACE). We create composite algorithms that comprise more than one individual maintenance algorithm in the hope that the strengths of one algorithm will compensate for the weaknesses of another. In MACE, we combine algorithms in two ways: either we put them in sequence so that one runs after the other, or we allow them to run separately and then vote as to whether a case should be deleted or not. We define a grammar that describes how these composites are created. We perform experiments based on 27 diverse datasets. Our results show that the MACE approach allows us to define algorithms with different trade-offs between accuracy and the amount of deletion.

Myxoid hepatic adenomas are a rare subtype of hepatic adenomas with distinctive deposition of extracellular myxoid material between the hepatic plates. A total of 9 cases were identified in 6 women and 3 men with an average of 59±12 years. The myxoid adenomas were single tumors in 5 cases and multiple in 4 cases. In 1 case with multiple adenomas, the myxoid adenoma arose in the background of GNAS-mutated hepatic adenomatosis. Myxoid hepatic adenomas had a high frequency of malignant transformation (N=5 cases). They were characterized at the molecular level by HNF1A inactivating mutations, leading to loss of LFABP protein expression. In addition, myxoid adenomas had recurrent mutations in genes within the protein kinase A (PKA) pathway or in genes that regulate the PKA pathway: GNAS, CDKN1B (encodes p27), and RNF123. In sum, myxoid adenomas are rare, occur in older-aged persons, have a high risk of malignant transformation, and are characterized by the combined inactivation of HNF1A and additional mutations that appear to cluster in the PKA pathway.

Abstract.We present what is, to the best of our knowledge, the first analysis that uses dataset complexity measures to evaluate case base editing algorithms. We select three different complexity measures and use them to evaluate eight case base editing algorithms. While we might expect the complexity of a case base to decrease, or stay the same, and the classification accuracy to increase, or stay the same, after maintenance, we find many counter-examples. In particular, we find that the RENN noise reduction algorithm may be over-simplifying class boundaries.

In Case-Based Reasoning (CBR), case base maintenance algorithms remove noisy or redundant cases from case bases. The best maintenance algorithm to use on a particular case base at a particular stage in a CBR system's lifetime will vary. In this paper, we propose a meta-case-based classifier for selecting the best maintenance algorithm. The classifier takes in a description of a case base that is to undergo maintenance, and uses meta-cases-descriptions of case bases that have undergone maintenance-to predict the best maintenance algorithm. For describing case bases, we use measures of dataset complexity. We present the results of experiments that show the classifier can come close to selecting the best possible maintenance algorithms.

The authors report the case of a 55-year-old patient with a chronic lower-limb wound thought to be secondary to vasculitis. This case illustrates the importance of maintaining a high index of suspicion for vasculitic ulcers in patients with autoimmune disease. Management considerations in this context are also discussed.