Artificial neural networks (ANNs) effectively analyze non-linear data sets. The aimed was A review of the relevant published articles that focused on the application of ANNs as a tool for assisting clinical decision-making in neurosurgery. A literature review of all full publications in English biomedical journals (1993-2013) was undertaken. The strategy included a combination of key words 'artificial neural networks', 'prognostic', 'brain', 'tumor tracking', 'head', 'tumor', 'spine', 'classification' and 'back pain' in the title and abstract of the manuscripts using the PubMed search engine. The major findings are summarized, with a focus on the application of ANNs for diagnostic and prognostic purposes. Finally, the future of ANNs in neurosurgery is explored. A total of 1093 citations were identified and screened. In all, 57 citations were found to be relevant. Of these, 50 articles were eligible for inclusion in this review. The synthesis of the data showed several applications of ANN in neurosurgery, including: (1) diagnosis and assessment of disease progression in low back pain, brain tumours and primary epilepsy; (2) enhancing clinically relevant information extraction from radiographic images, intracranial pressure processing, low back pain and real-time tumour tracking; (3) outcome prediction in epilepsy, brain metastases, lumbar spinal stenosis, lumbar disc herniation, childhood hydrocephalus, trauma mortality, and the occurrence of symptomatic cerebral vasospasm in patients with aneurysmal subarachnoid haemorrhage; (4) the use in the biomechanical assessments of spinal disease. ANNs can be effectively employed for diagnosis, prognosis and outcome prediction in neurosurgery.
Object The purpose of this study was to develop an artificial neural network (ANN) model for predicting 2-year surgical satisfaction, and to compare the new model with traditional predictive tools in patients with lumbar spinal canal stenosis. Methods The 2 prediction models included an ANN and a logistic regression (LR) model. The patient age, sex, duration of symptoms, walking distance, visual analog scale scores of leg pain or numbness, the Japanese Orthopaedic Association score, the Neurogenic Claudication Outcome Score, and the stenosis ratio values were determined as the input variables for the ANN and LR models that were developed. Patient surgical satisfaction was recorded using a standardized measure. The ANNs were fed patient data to predict 2-year surgical satisfaction based on several input variables. Sensitivity analysis was applied to the ANN model to identify the important variables. The receiver operating characteristic–area under curve (ROC-AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated for evaluating the 2 models. Results A total of 168 patients (59 male, 109 female; mean age 59.8 ± 11.6 years) were divided into training (n = 84), testing (n = 42), and validation (n = 42) data sets. Postsurgical satisfaction was 88.7% at 2-year follow-up. The stenosis ratio was the important variable selected by the ANN. The ANN model displayed a better accuracy rate in 96.9% of patients, a better Hosmer-Lemeshow statistic in 42.4% of patients, and a better ROC-AUC in 80% of patients, compared with the LR model. Conclusions The findings show that an ANN can predict 2-year surgical satisfaction for use in clinical application and is more accurate compared with an LR model.
Thalamotomy significantly suppressed essential tremor in 86% of patients and restored the ability to hold a glass to drink in 81% in the long term, but tremor recurred in 5/21 patients up to 5 years postoperatively, unlike parkinsonian patients whose tremor seldom recurs after 3 months. In multiple sclerosis (MS), 67% of those followed showed sustained significant suppression of tremor, 67% sustained improvement in dexterity, 50% in drinking; tremor recurred up to 5 years postoperatively. In other cerebellar tremors, 52% of those followed enjoyed lasting significant relief of tremor, 55% in dexterity, 45 % in drinking, tremor relief being best in poststroke cases. Chronic thalamic stimulation may be the preferred therapy in MS and other cerebellar tremors.
The findings show that an ANNs can be used to predict the diagnostic statues of recurrent and nonrecurrent group of LDH patients before the first or index microdiscectomy.
Study DesignCross-sectional.PurposeTo translate and culturally adapt an Iranian version of the Pain Sensitivity Questionnaire (PSQ) in Iran.Overview of LiteratureInstruments measuring patient reported outcomes should satisfy certain psychometric properties.MethodsThe PSQ was translated following cross-cultural adaptation guidelines. A total of 101 patients with lumbar disc herniation (LDH), and 39 healthy cases were included in the study. All participants completed the PSQ and the Pain Catastrophizing Scale (PCS). The internal consistency, test-retest reliability, known group comparison, criterion validity and item-scale correlations were assessed.ResultsThe mean age of participants was 51.7 years. Reliability, validity and correlation of PSQ and PCS showed satisfactory results. Cronbach's alpha coefficients were 0.81 for PSQ-total, 0.82 for PSQ-minor, and 0.82 for PSQ-moderate. The intraclass correlation coefficients value was 0.84 (0.616–0.932) indicating an excellent test-retest reliability. The instrument discriminated well between sub-groups of patients who differed in a standard predictive measure of LDH surgery (the Finneson–Cooper score). Total PSQ were also significantly correlated with the total scores of the PCS, lending support to its good convergent validity. Additionally, the correlation of each item with its hypothesized domain on the PSQ indicated acceptable results, suggesting that the items had a substantial relationship with their own domains.ConclusionsThe adapted Iranian PSQ is a valid and reliable questionnaire for the assessment of pain in patients with LDH.
In the present study, a classification of functional near-infrared spectroscopy (fNIRS) based on support vector machine (SVM) is presented. It is a non-invasive method monitoring human brain function by evaluating the concentration variation of oxy-hemoglobin and deoxy-hemoglobin. fNIRS is a functional optical imaging technology that measures the neural activities and hemodynamic responses in brain. The data were gathered from 11 healthy volunteers and 16 schizophrenia of the same average age by a 16-channel fNIRS (NIROXCOPE 301 system developed at the Neuro-Optical Imaging Laboratory, continuous-wave dual wavelength). Schizophrenia is a mental disorder that is characterized by mental processing collapse and weak emotional responses. This mental disorder is usually accompanied by a serious disturbance in social and occupational activities. The signals were initially preprocessed by DWT to remove any systemic physiological impediment. A preliminary examination by the genetic algorithm (GA) suggested that some channels of the recreated fNIRS signals required further investigation. The energy of these recreated channel signals was computed and utilized for signal arrangement. We used SVM-based classifier to determine the cases of schizophrenia. The result of six channels is higher than 16 channels. The results demonstrated a classification precision of about 87% in the discovery of schizophrenia in the healthy subjects.
Abstract:Background: Lumbar Disc Herniation (LDH) and Lumbar Spinal Stenosis (LSS) are the most common diagnoses of low back and leg pain symptoms. The Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ) is a measure of health related quality of life in these patients. This study aimed to cross-culturally translate and validate the JOABPEQ in Iran. Methods: This was a prospective clinical validation trial. The translation and cross-cultural adaptation of the original questionnaire were performed in accordance with the published guidelines. A total of 103 patients with LDH or LSS were asked to respond to the questionnaire at two time points: pre-and post-operation (pre-and post-operative assessments) and were followed up for 6 months. To evaluate the reliability the internal consistency was assessed using the Cronbach's alpha coefficient and validity was assessed using the convergent validity. Responsiveness to the clinical change also was assessed comparing patients' pre-and postoperative scores. Results: The Cronbach's alpha coefficients for the JOABPEQ at preoperative and postoperative assessments ranged from 0.71 to 0.81 indicating a good internal consistency for the questionnaire. Furthermore, the correlation of each item with its hypothesized subscale of the JOABPEQ showed satisfactory results suggesting that the items had a substantial association with the subscale representing the concept. Further analysis also indicated that the questionnaire was responsive to change (P less than 0.0001). Conclusions: In conclusion, the Iranian version of JOABPEQ performed well and the findings suggest that it is a reliable and valid measure of back pain evaluation among LDH and LCS patients.
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