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Decision tree neurology

Ryan W R Guilbault, Marcus Andreas Ohlsson, Anna M Afonso, Mark H Ebell
OBJECTIVE: To prospectively validate a previously developed classification and regression tree (CART) model that predicts the likelihood of a good outcome among patients undergoing inpatient cardiopulmonary resuscitation. DESIGN: Prospective validation of a clinical decision rule. SETTING: Skåne University Hospital in Malmo, Sweden. PATIENTS: All adult patients (N = 287) experiencing in-hospital cardiopulmonary arrest and undergoing cardiopulmonary resuscitation between 2007 and 2010...
January 1, 2017: Journal of Intensive Care Medicine
David Barbic, Brian Klinkenberg, Brian Grunau, Jim Christenson
OBJECTIVE: No prior work exists examining the relation between the geographic distribution of out-of-hospital cardiac arrest (OHCA) in the city of Vancouver and surrounding areas that may exhibit a clustering of cases. The primary objective of this study was to describe the distribution of OHCA within the Vancouver Coastal Health region using a geographic information system (GIS) analysis and appropriate statistical analyses. METHODS: This study was a post-hoc GIS-based analysis of OHCA patients in the city of Vancouver and surrounding areas, using data collected by the Resuscitation Outcomes Consortium between September 2007 and December 2011...
October 17, 2016: CJEM
Ying Zheng, Feng Pan, Sonja Sorensen
As the number of interventions available in a therapeutic area increases, the relevant decision questions in health technology assessment (HTA) expand to compare treatment sequences instead of discrete treatments and identify optimal sequences or position for a particular treatment in a sequence. The objective of this work was to review approaches used to model treatment sequences and provide practical guidance on conceptualizing whether and how to model sequences in health economic models. Economic models including treatment sequencing assessed by the National Institute for Health and Care Excellence were reviewed, as these assessments generally provide both policy relevance and comprehensive model detail...
January 2017: PharmacoEconomics
Andrzej W Przybyszewski, Mark Kon, Stanislaw Szlufik, Artur Szymanski, Piotr Habela, Dariusz M Koziorowski
We still do not know how the brain and its computations are affected by nerve cell deaths and their compensatory learning processes, as these develop in neurodegenerative diseases (ND). Compensatory learning processes are ND symptoms usually observed at a point when the disease has already affected large parts of the brain. We can register symptoms of ND such as motor and/or mental disorders (dementias) and even provide symptomatic relief, though the structural effects of these are in most cases not yet understood...
September 14, 2016: Sensors
B Brüggenjürgen, T Baker, R Bhogal, F Ahmed
BACKGROUND: Chronic migraine (CM) is a neurological disorder associated with substantial disability. Botulinum toxin type A (Botox) is an approved and effective preventive treatment option for adult patients with CM. Transcranial magnetic stimulation (TMS) is an alternative treatment device delivering a brief pre-set magnetic pulse used for self-administration by the patient at home. Despite being available in a risk share scheme TMS is perceived to be more costly in the UK. The objective of this study was to analyse the incremental costs of TMS compared to Botox in refractory CM patients both for a UK individual funding request setting as well as for an average UK specialist center setting...
2016: SpringerPlus
Benjamin W Y Lo, Hitoshi Fukuda, Mark Angle, Jeanne Teitelbaum, R Loch Macdonald, Forough Farrokhyar, Lehana Thabane, Mitchell A H Levine
BACKGROUND: Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). METHODS: The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm...
2016: Surgical Neurology International
Nataliya Tkachenko, Kanwaljit Singh, Nicolas Abreu, Anne Marie Morse, Christy Day, Kathyrn Fitzgerald, Mikhail Kazachkov, Sanjeev Kothare
BACKGROUND: Children with medical complexity have a high prevalence of sleep disorders. However, outpatient polysomnography to evaluate for these conditions may be difficult to perform because of lack of skilled nursing care. The aim of this study was to explore polysomnography indications in hospitalized children and assess its impact on patient care. METHODS: Data from 85 inpatient polysomnographies of 70 children hospitalized between March and December 2014 were retrospectively collected...
April 2016: Pediatric Neurology
Kabir Yadav, Efsun Sarioglu, Hyeong Ah Choi, Walter B Cartwright, Pamela S Hinds, James M Chamberlain
BACKGROUND: The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. OBJECTIVES: To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports...
February 2016: Academic Emergency Medicine: Official Journal of the Society for Academic Emergency Medicine
Inge-Marie Velstra, Marc Bolliger, Jörg Krebs, Johan S Rietman, Armin Curt
OBJECTIVE: To determine which single or combined upper limb muscles as defined by the International Standards for the Neurological Classification of Spinal Cord Injury (ISNCSCI); upper extremity motor score (UEMS) and the Graded Redefined Assessment of Strength, Sensibility, and Prehension (GRASSP), best predict upper limb function and independence in activities of daily living (ADLs) and to assess the predictive value of qualitative grasp movements (QlG) on upper limb function in individuals with acute tetraplegia...
May 2016: Neurorehabilitation and Neural Repair
Parimal Kulkarni, L Douglas Smith, Keith F Woeltje
We compare statistical approaches for predicting the likelihood that individual patients will require readmission to hospital within 30 days of their discharge and for setting quality-control standards in that regard. Logistic regression, neural networks and decision trees are found to have comparable discriminating power when applied to cases that were not used to calibrate the respective models. Significant factors for predicting likelihood of readmission are the patient's medical condition upon admission and discharge, length (days) of the hospital visit, care rendered during the hospital stay, size and role of the medical facility, the type of medical insurance, and the environment into which the patient is discharged...
September 2016: Health Care Management Science
Junichiro Satomi, A Ammar Ghaibeh, Hiroki Moriguchi, Shinji Nagahiro
OBJECT: The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors...
July 2015: Journal of Neurosurgery
S V Tiaglyĭ
Results of examination and surgical treatment for glial tumors of fronto-temporal localization in 40 patients of both gender and different age, duration of treatment, somatic state were analyzed. Complex clinico-neurological examination of patients have included neurovisualized methods of investigation: angiography of carotid arteries, computeric and a magnet resonance tomography. Algorithm of preoperative diagnosis was elaborated for the surgical tactics establishment.
October 2014: Klinichna Khirurhiia
Lorenzo G Tanadini, Torsten Hothorn, Linda A T Jones, Daniel P Lammertse, Rainer Abel, Doris Maier, Rüdiger Rupp, Norbert Weidner, Armin Curt, John D Steeves
BACKGROUND: Several novel drug- and cell-based potential therapies for spinal cord injury (SCI) have either been applied or will be considered for future clinical trials. Limitations on the number of eligible patients require trials be undertaken in a highly efficient and effective manner. However, this is particularly challenging when people living with incomplete SCI (iSCI) represent a very heterogeneous population in terms of recovery patterns and can improve spontaneously over the first year after injury...
October 2015: Neurorehabilitation and Neural Repair
L Gatin, N Khouri
INTRODUCTION: Patients with neurological disorders often exhibit dislocation or subluxation of the hip. Anterior dislocation is rare, little known, and often associated with deformities. Its surgical treatment has rarely been studied. HYPOTHESIS: Hip surgery (with open reduction, femoral and pelvic osteotomy, and adapted tenotomies) could provide a centered hip that is supple and painless. MATERIALS AND METHODS: Ten hips (seven dislocated, three subluxated) in six patients with a mean age of 8...
February 2015: Orthopaedics & Traumatology, Surgery & Research: OTSR
Pitamber Shukla, Ishita Basu, Daniela Tuninetti
Deep Brain Stimulation (DBS) is a surgical procedure to treat some progressive neurological movement disorders, such as Essential Tremor (ET), in an advanced stage. Current FDA-approved DBS systems operate open-loop, i.e., their parameters are unchanged over time. This work develops a Decision Tree (DT) based algorithm that, by using non-invasively measured surface EMG and accelerometer signals as inputs during DBS-OFF periods, classifies the ET patient's state and then predicts when tremor is about to reappear, at which point DBS is turned ON again for a fixed amount of time...
2014: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Weiting Chen, Yu Wang, Guitao Cao, Guoqiang Chen, Qiufang Gu
BACKGROUND: Modern medical advances have greatly increased the survival rate of infants, while they remain in the higher risk group for neurological problems later in life. For the infants with encephalopathy or seizures, identification of the extent of brain injury is clinically challenging. Continuous amplitude-integrated electroencephalography (aEEG) monitoring offers a possibility to directly monitor the brain functional state of the newborns over hours, and has seen an increasing application in neonatal intensive care units (NICUs)...
2014: Biomedical Engineering Online
Yoshikazu Goto, Tetsuo Maeda, Yumiko Nakatsu-Goto
INTRODUCTION: At hospital arrival, early prognostication for children after out-of-hospital cardiac arrest (OHCA) might help clinicians formulate strategies, particularly in the emergency department. In this study, we aimed to develop a simple and generally applicable bedside tool for predicting outcomes in children after cardiac arrest. METHODS: We analyzed data of 5,379 children who had undergone OHCA. The data were extracted from a prospectively recorded, nationwide, Utstein-style Japanese database...
2014: Critical Care: the Official Journal of the Critical Care Forum
C Saegerman, A Alba-Casals, I García-Bocanegra, F Dal Pozzo, G van Galen
West Nile fever (WNF) is a viral zoonotic infection caused by a mosquito-borne flavivirus of the Flaviviridae family. According to a comparative study, the passive surveillance of horses by equine veterinarians appeared to be the most cost-effective system in the European context of WNF. Clinical data issued from a passive epidemiosurveillance network from September 2010 to December 2011 on horses in Spain were statistically compared and used to develop a predictive diagnostic decision tree, both with the aim to improve the early clinical detection of WNF in horses...
April 2016: Transboundary and Emerging Diseases
Baha Şen, Musa Peker, Abdullah Çavuşoğlu, Fatih V Çelebi
Sleep scoring is one of the most important diagnostic methods in psychiatry and neurology. Sleep staging is a time consuming and difficult task undertaken by sleep experts. This study aims to identify a method which would classify sleep stages automatically and with a high degree of accuracy and, in this manner, will assist sleep experts. This study consists of three stages: feature extraction, feature selection from EEG signals, and classification of these signals. In the feature extraction stage, it is used 20 attribute algorithms in four categories...
March 2014: Journal of Medical Systems
Timothy M Gersch, Nicholas C Foley, Ian Eisenberg, Jacqueline Gottlieb
Empirical studies of decision making have typically assumed that value learning is governed by time, such that a reward prediction error arising at a specific time triggers temporally-discounted learning for all preceding actions. However, in natural behavior, goals must be acquired through multiple actions, and each action can have different significance for the final outcome. As is recognized in computational research, carrying out multi-step actions requires the use of credit assignment mechanisms that focus learning on specific steps, but little is known about the neural correlates of these mechanisms...
2014: PloS One
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