An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

MHCPEP, a database of MHC-binding peptides: update 1997

MHCPEP (http://wehih.wehi.edu.au/mhcpep/) is a curated database comprising over 13 000 peptide sequences known to bind MHC molecules, Entries are compiled from published reports as well as from direct submissions of experimental data, Each entry contains the peptide sequence, its MHC specificity and where available, experimental method, observed activity, binding affinity, source protein and anchor positions, as well as publication references, The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using WWW or FTP.

An update on genetic, structural and functional studies of arylamine N-acetyltransferases in eucaryotes and procaryotes

Arylamine N-acetyltransferase (NAT) was first identified as the inactivator of the anti-tubercular drug isoniazid, The enzyme was shown to catalyse the transfer of an acetyl group from acetyl-CoA to the terminal nitrogen of the hydrazine drug. The rate of inactivation of isoniazid was polymorphically distributed in the population and was one of the first examples of pharmacogenetic variation, NAT was identified recently in Mycobacterium tuberculosis and is a candidate for; modulating the response to isoniazid, Genome sequences have revealed many homologous members of this unique family of enzymes. The first three-dimensional structure of a member of the NAT family identifies a catalytic triad consisting of aspartate, histidine and cysteine proposed to form the activation mechanism. So far, all procaryotic NATs resemble the human enzyme which acetylates isoniazid (NAT2), Human NAT2 is characteristic of drug-metabolizing enzymes: it is found in liver and intestine, In humans and other mammals, there are up to three different isoenzymes. If only one isoenzyme is present, it is like human NAT1. Human NAT1 and its murine equivalent specifically acetylate the folate catabolite p-amino-benzoylglutamate. NAT1 and its murine homologue each have a ubiquitous tissue distribution and are expressed early in development at the blastocyst stage, During murine embryonic development, NAT is expressed in the developing neural tube. The proposed endogenous role of NAT in folate metabolism, and its multi-allelic nature, indicate that its role in development should be assessed further.

MHCPEP, a database of MHC-binding peptides: Update 1996

MHCPEP is a curated database comprising over 9000 peptide sequences known to bind MHC molecules. Entries are compiled from published reports as well as from direct submissions of experimental data. Each entry contains the peptide sequence, its MHC specificity and, when available, experimental method, observed activity, binding affinity, source protein, anchor positions and publication references. The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using WWW, FTP or Gopher.

Papillomavirus research update: highlights of the Barcelona HPV 2000 international papillomavirus conference

The 18th international papillomavirus conference took place in Barcelona, Spain in July 2000. The HPV clinical workshop was jointly organised with the annual meeting of the Spanish Association of Cervical Pathology and Colposcopy. The conference included 615 abstracts describing ongoing research in epidemiology, diagnosis/screening, treatment/prognosis, immunology/human immunodeficiency virus, vaccine development/trials, transformation/progression, replication, transcription/translation, viral protein functions, and viral and host interactions. This leader summarises the highlights presented at the conference (the full text of the abstracts and lectures can be found at www.hpv2000.com). Relevant material in Spanish can be found at www.aepcc. org.

Incremental parsing in language-based editors: user needs and how to meet them

Incremental parsing has long been recognized as a technique of great utility in the construction of language-based editors, and correspondingly, the area currently enjoys a mature theory. Unfortunately, many practical considerations have been largely overlooked in previously published algorithms. Many user requirements for an editing system necessarily impact on the design of its incremental parser, but most approaches focus only on one: response time. This paper details an incremental parser based on LR parsing techniques and designed for use in a modeless syntax recognition editor. The nature of this editor places significant demands on the structure and quality of the document representation it uses, and hence, on the parser. The strategy presented here is novel in that both the parser and the representation it constructs are tolerant of the inevitable and frequent syntax errors that arise during editing. This is achieved by a method that differs from conventional error repair techniques, and that is more appropriate for use in an interactive context. Furthermore, the parser aims to minimize disturbance to this representation, not only to ensure other system components can operate incrementally, but also to avoid unfortunate consequences for certain user-oriented services. The algorithm is augmented with a limited form of predictive tree-building, and a technique is presented for the determination of valid symbols for menu-based insertion. Copyright (C) 2001 John Wiley & Sons, Ltd.