Biomedical subjects

Steven Walczak

Publications and source records attributed to Steven Walczak.

4 recordsLinked to original sources

PubMed2005

Artificial neural network medical decision support tool: predicting transfusion requirements of ER patients.

Blood product transfusion is a financial concern for hospitals and patients. Efficient utilization of this dwindling resource is a critical problem if hospitals are to maximize patient care while minimizing costs. Traditional statistical models do not perform well in this domain. An additional concern is the speed with which transfusion decisions and planning can be made. Rapid assessment in the emergency room (ER) necessarily limits the amount of usable information available (with respect to independent variables available). This study evaluates the efficacy of using artificial neural networks (ANNs) to predict the transfusion requirements of trauma patients using readily available information. A total of 1016 patient records are used to train and test a backpropagation neural network for predicting the transfusion requirements of these patients during the first 2, 2-6, and 6-24 h, and for total transfusions. Sensitivity and specificity analysis are used along with the mean absolute difference between blood units predicted and units transfused to demonstrate that ANNs can accurately predict most ER patient transfusion requirements, while only using information available at the time of entry into the ER.

Blood Transfusion↗

PubMed2003

A multiagent architecture for developing medical information retrieval agents.

Information that is available on the world wide web (WWW) is already more vast than can be comprehensibly studied by individuals and this quantity is increasing at a staggering pace. The quality of service delivered by physicians is dependent on the availability of current information. The agent paradigm offers a means for enabling physicians to filter information and retrieve only information that is relevant to current patient treatments. As with many specialized domains, agent-based information retrieval in medical domains must satisfy several domain-dependent constraints. A multiple agent architecture is developed and described in detail to efficiently provide agent-based information retrieval from the WWW and other explicit information resources. A simulation of the proposed multiple agent architecture shows a 97% decrease in information overload and an 85% increase in information relevancy over existing meta-search tools (with even larger gains over standard search engines).

Artificial Intelligence↗

PubMed2003

Factors affecting transfusion of fresh frozen plasma, platelets, and red blood cells during elective coronary artery bypass graft surgery.

CONTEXT: The ability to predict the use of blood components during surgery will improve the blood bank's ability to provide efficient service. OBJECTIVE: Develop prediction models using preoperative risk factors to assess blood component usage during elective coronary artery bypass graft surgery (CABG). DESIGN: Eighty-three preoperative, multidimensional risk variables were evaluated for patients undergoing elective CABG-only surgery. MAIN OUTCOMES MEASURES: The study endpoints included transfusion of fresh frozen plasma (FFP), platelets, and red blood cells (RBC). Multivariate logistic regression models were built to assess the predictors related to each of these endpoints. SETTING: Department of Veterans Affairs (VA) health care system. PATIENTS: Records for 3034 patients undergoing elective CABG-only procedures; 1033 patients received a blood component transfusion during CABG. RESULTS: Previous heart surgery and decreased ejection fraction were significant predictors of transfusion for all blood components. Platelet count was predictive of platelet transfusion and FFP utilization. Baseline hemoglobin was a predictive factor for more than 2 units of RBC. Some significant hospital variation was noted beyond that predicted by patient risk factors alone. CONCLUSIONS: Prediction models based on preoperative variables may facilitate blood component management for patients undergoing elective CABG. Algorithms are available to predict transfusion resources to assist blood banks in improving responsiveness to clinical needs. Predictors for use of each blood component may be identified prior to elective CABG for VA patients.

Blood Loss, Surgical↗

PubMed2002

Clinical correlate of EEG rhythmicity.

The widespread use of the routine EEG in clinical practice was a major development in the treatment of patients with ill-defined spells thought to be epileptic. Not every finding on the EEG is suggestive of epilepsy, and the EEG is subject to over-interpretation, which may lead to misdiagnosis and incorrect treatment. Although supplemented by other procedures, the EEG remains a cost-effective and noninvasive way to diagnose spells. To enhance further the diagnostic use of the EEG, it is important to determine how strongly patterns are correlated with clinical seizures. The authors studied one EEG pattern, lateralized bursts of theta, and found the rhythmicity of the pattern to be most strongly correlated with seizures.

Brain Injuries↗