Biomedical subjects

Cristiana Larizza

Publications and source records attributed to Cristiana Larizza.

7 recordsLinked to original sources

PubMed2005

Temporal data mining for the quality assessment of hemodialysis services.

OBJECTIVE: This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. METHODS: Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. RESULTS: We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. CONCLUSION: The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

Algorithms↗

PubMed2005

TA-clustering: cluster analysis of gene expression profiles through Temporal Abstractions.

This paper describes a new technique for clustering short time series of gene expression data. The technique is a generalization of the template-based clustering and is based on a qualitative representation of profiles which are labelled using trend Temporal Abstractions (TAs); clusters are then dynamically identified on the basis of this qualitative representation. Clustering is performed in an efficient way at three different levels of aggregation of qualitative labels, each level corresponding to a distinct degree of qualitative representation. The developed TA-clustering algorithm provides an innovative way to cluster gene profiles. We show the developed method to be robust, efficient and to perform better than the standard hierarchical agglomerative clustering approach when dealing with temporal dislocations of time series. Results of the TA-clustering algorithm can be visualized as a three-level hierarchical tree of qualitative representations and as such easy to interpret. We demonstrate the utility of the proposed algorithm on a set of two simulated data sets and on a study of gene expression data from S. cerevisiae.

Algorithms↗

PubMed2004

Management of patients with diabetes through information technology: tools for monitoring and control of the patients' metabolic behavior.

BACKGROUND: The junction of telemedicine home monitoring with multifaceted disease management programs seems nowadays a promising direction to combine the need for an intensive approach to deal with diabetes and the pressure to contain the costs of the interventions. Several projects in the European Union and the United States are implementing information technology-based services for diabetes management using a comprehensive approach. Within these systems, the role of tools for data analysis and automatic reminder generation seems crucial to deal with the information overload that may result from large home monitoring programs. The objective of this study was to describe the automatic reminder generation system and the summary indicators used in a clinical center within the telemedicine project M2DM, funded by the European Commission, and to show their usage during a 7-month on-field testing period. METHODS: M2DM is a multi-access service for management of patients with diabetes. The basic functionality of the technical service includes a Web-based electronic medical record and messaging system, a computer telephony integration service, a smart-modem located at home, and a set of specialized software modules for automated data analysis. The information flow is regulated by a software scheduler, called the Organizer, that, on the basis of the knowledge on the health care organization, is able to automatically send e-mails and alerts notifications as well as to commit activities to software agents, such as data analysis. Thanks to this system, it was possible to define an automatic reminder system, which relies on a data analysis tool and on a number of technologies for communication. Within the M2DM system, we have also defined and implemented a number of indexes able to summarize the patients' day-by-day metabolic control. In particular, we have defined the global risk index (GRI) of developing microangiopathic complications. RESULTS: The system for generating automatic alarms and reminders coupled with the indexes for evaluating the patients' metabolic control has been used for 7 months at the Fondazione Salvatore Maugeri (FSM) in Pavia, Italy. Twenty-two patients (43 +/- 16 years old, 12 men and 10 women) have been involved; six dropped out from the study. The average number of monthly automatic messages was 29.44 +/- 9.83, i.e., about 1.8 messages per patient per month. The number of monthly alarm reminders generated by the system was 16.44 +/- 4.39, so that the number of alarms per patient was about 1. The number of messages sent by patients and physicians during the project was about 13 per month. The GRI analysis shows, during the last trimester, a slight improvement of the performance of the FSM clinic, with a decrease in the percentage of badly controlled values from 33% to 27%. Finally, we found the presence of a linear increasing correlation between the mean GRI values and the number of alarms generated by the system. CONCLUSIONS: A telemedicine system may incorporate features that make it a suitable technological backbone for implementing a disease management program. The availability of data analysis tools, automated messaging system, and summary indicators of the effectiveness of the health care program may help in defining efficient clinical interventions.

Diabetes Mellitus↗

PubMed2004

A careflow management system for chronic patients.

The management of chronic patients is a complex process, which requires the cooperation of all primary care professionals and their interaction with specialists, laboratories and personnel of different organizations. In this paper we show how a Careflow Management System (CfMS) may represent an essential component of an innovative Health Information System (HIS) able to handle the information and communication needs underlying chronic diseases management. On the basis of a general architecture designed for chronic diseases, we describe a CfMS implementation in the area of diabetes management; such a system embeds EPR and telemedicine functionalities as end-users applications as well as a module for inter-organizational communication based on contracts and on XML messages.

Case Management↗

PubMed2003

Design, methods, and evaluation directions of a multi-access service for the management of diabetes mellitus patients.

Recent advances in information and communication technology allow the design and testing of new models of diabetes management, which are able to provide assistance to patients regardless of their distance from the health care providers. The M2DM project, funded by the European Commission, has the specific aim to investigate the potential of novel telemedicine services in diabetes management. A multi-access system based on the integration of Web access, telephone access through interactive voice response systems, and the use of palmtops and smart modems for data downloading has been implemented. The system is based on a technological platform that allows a tight integration between the access modalities through a middle layer called the multi-access organizer. Particular attention has been devoted to the design of the evaluation scheme for the system: A randomized controlled study has been defined, with clinical, organizational, economic, usability, and users' satisfaction outcomes. The evaluation of the system started in January 2002. The system is currently used by 67 patients and seven health care providers in five medical centers across Europe. After 6 months of usage of the system no major technical problems have been encountered, and the majority of patients are using the Web and data downloading modalities with a satisfactory frequency. From a clinical viewpoint, the hemoglobin A1c (HbA1c) of both active patients and controls decreased, and the variance of HbA1c in active patients is significantly lower than the control ones. The M2DM system allows for the implementation of an easy-to-use, user-tailored telemedicine system for diabetes management. The first clinical results are encouraging and seem to substantiate the hypothesis of its clinical effectiveness.

Diabetes Mellitus↗

PubMed2003

Telemedicine in the management of young patients with type 1 diabetes mellitus: a follow-up study.

DCCT (Diabetes Control and Complications Trial) study showed that tight metabolic control of diabetes mellitus can delay the onset and/or reduce the frequency of vascular complications. Telemedicine, i.e. telecommunications and information technologies in health care, is a useful tool to achieve the DCCT goals. Our European Community (EC) sponsored Telematic management of Insulin-Dependent Diabetes Mellitus (T-IDDM) project implements a telemedicine service through on a careful analysis of current medical practice. The system is based on two components: Patient Unit (PU) and Medical Unit (MU) connected by a Telecommunication system (TS). PU allows data collection and transmission from the patient's house to the hospital, assists self-monitoring activity and suggests insulin variations. PU communicates patient's current metabolic state the MU. MU assists the physician in periodic evaluation and suggests the prescriptions to communicate back defining a treatment protocol. TS system is based on telephone lines, relying on the Intranet technology. To test the system functionality and potential impact in type 1 diabetes clinical practice, we enrolled 6 patients (4 males and 2 females), aged 9.9-15.8 yrs, with disease duration 2.1-6.4 yrs, intensively treated. One girl run out after a 1-year follow-up HbA1c levels decreased, but not significantly. Insulin requirement reduced, significantly in 2 patients (p = 0.02 and p = 0.07). A positive correlation was between number of links and protocol changes (p = 0.01), between number of protocols changes and HbA1c decrease (p = 0.02). In pediatric patients periodical visits are necessary, but T-IDDM enables continuity of care improving access and activities. An index is represented by the high number of messages between the 2 Units, seeming weekly exchange.

Adolescent↗

PubMedDate not supplied

Integrating model-based decision support in a multi-modal reasoning system for managing type 1 diabetic patients.

We present a multi-modal reasoning (MMR) methodology that integrates case-based reasoning (CBR), rule-based reasoning (RBR) and model-based reasoning (MBR), meant to provide physicians with a reliable decision support tool in the context of type 1 diabetes mellitus management. In particular, we have implemented a decision support system that is able to jointly exploit a probabilistic model of the glucose-insulin system at the steady state, a RBR system for suggestion generation and a CBR system for patient's profiling. The integration of the CBR, RBR and MBR paradigms allows for an optimized exploitation of all the available information, and for the definition of a therapy properly tailored to the patient's needs, overcoming the single approaches limitations. The system has been tested both on simulated and on real patients' data.

Artificial Intelligence↗