11 research outputs found
Advances in traumatic brain injury research in 2020: A review article
No full textPerhaps in no other area of neurosurgery, has a greater research been done as in traumatic brain injury (TBI). Despite this, TBI remains one of the biggest killers around the world and especially in India. Decompressive craniotomy still remains one of the mainstay paradigms in the management of TBI. The following article explores several new modalities of treatment, and these include the role of beta-blockers for TBI, updates on decompressive craniotomy, the results of DECRA and RESCUEicp trials, diagnostic and prognostic biomarkers in TBI, vascular dysfunction, neuroimaging, and role of neuroinflammation in TBI
Development and Application of bundle-valued forms in hybrid mimetic spectral element method: Application to Linear elasticity
No full textOne of the novel methodologies in computational physics research is to use mimetic discretisation techniques. Among these, the mimetic spectral element method holds special promise as it not only has the benefits of mimetic methods but also the additional benefit of higher-order discretisations using higher polynomial degrees. These methods are aided by the development of algebraic dual polynomials, resulting in a sparser system for better computational efficiency. This combination was used to develop a formulation that would result in topological relations for equilibrium of forces as well as the symmetry of the stress tensor for linear elasticity as well as the first steps for Stokes flows in an orthogonal domain. As a result, this study was extended to look at how a modified formulation would behave for an unsteady linear elastic solid, with the intention to extend this method to Fluid-Structure Interaction cases. However, the choice of both primal and nodal basis functions makes it impossible to undertake this challenge, demanding a rethink in strategy towards looking at linear elastic solids when the physical domain is not orthogonal. With the use of bundle-valued forms to represent physical quantities, a new hybrid formulation is developed where the equivalent of the physical problem is computed on a reference domain, which is orthogonal and thus can utilise the spectral bases defined before. The physical problem is defined on a skewed domain, where partial transformation of components results in a formulation that can conserve linear momentum point-wise, but not conservation of angular momentum, although angular momentum does converge on refinement of polynomial degree and mesh parameters. A change in bases with partial transformation aiming to make angular momentum conservation topological is not fruitful, although the value of the error decreases in the process. The final attempt is through full transformation, which results in a formulation with an inherent error in the formulation, owing to erroneous assumptions.Aerospace Engineerin
Multi-class and Multi-label classication of Darkweb Data
No full textabstract: In this research, I try to solve multi-class multi-label classication problem, where
the goal is to automatically assign one or more labels(tags) to discussion topics seen
in deepweb. I observed natural hierarchy in our dataset, and I used dierent
techniques to ensure hierarchical integrity constraint on the predicted tag list. To
solve `class imbalance' and `scarcity of labeled data' problems, I developed semisupervised
model based on elastic search(ES) document relevance score. I evaluate
our models using standard K-fold cross-validation method. Ensuring hierarchical
integrity constraints improved F1 score by 11.9% over standard supervised learning,
while our ES based semi-supervised learning model out-performed other models in
terms of precision(78.4%) score while maintaining comparable recall(21%) score.Dissertation/ThesisMasters Thesis Computer Science 201
Factors predicting loss of cervical lordosis following cervical laminoplasty: A critical review
No full textImpact of different visualization devices on accuracy, efficiency, and dexterity in neurosurgery: a laboratory investigation
No full textOBJECTIVE
Extracorporeal telescopes (exoscopes) have been the latest addition to the neurosurgeons’ armamentarium, acting as a bridge between operating microscopes and endoscopes. However, to the authors’ knowledge there are no published preclinical laboratory studies of the accuracy, efficiency, and dexterity of neurosurgical training for the use of 2D or 3D exoscopes compared with microscopes.
METHODS
In a controlled experimental setup, 22 participating neurosurgery residents performed simple (2D) and complex (3D) motor tasks with three visualization tools in alternating sequence: a 2D exoscope, 3D exoscope, and microscope, using a block randomization model based on the neurosurgeons’ prior training experience (novice, intermediate, and senior: n = 6, 12, and 4, respectively). Performance scores (PS; including error and efficiency scores) and dexterity scores (DS) were calculated to objectify the accuracy, efficiency, and finesse of task performance. Repeated measures ANOVA analysis was used to compare the PS, DS, and cumulative scores (CS) of candidates using the three visualization aids. Bland-Altman plots and intraclass correlation coefficients were generated to quantify intraobserver and interobserver agreement for DS. Subgroup analysis was performed to assess the impact of participants’ prior training. A postexercise survey was conducted to assess the comfort level (on a 10-point analog scale) of the participants while using each visualization tool for performing the suturing task.
RESULTS
PS, DS, and CS were significantly impacted by the visualization tool utilized for 2D motor tasks (p < 0.001 for each), with the microscope faring better than the 2D exoscope (p = 0.04) or 3D exoscope (p = 0.008). The PS for the 3D object transfer task was significantly influenced by the visualization aid used (p = 0.007), with the microscope and 3D exoscope faring better than the 2D exoscope (p = 0.04 for both). The visualization instrument used significantly affected the DS and CS for the suturing task (p < 0.001 for both), with the microscope again scoring better than the 2D exoscope (p < 0.001) or 3D exoscope (p = 0.005). The impact of the visualization aid was more apparent in participants with a shorter duration of residency (novice, p = 0.03; intermediate, p = 0.0004). Participants also felt the greatest operational comfort while working with a microscope, 3D exoscope, and 2D exoscope, in that order (p < 0.0001).
CONCLUSIONS
Compared with 3D and 2D exoscopes, an operating microscope provides better dexterity and performance and a greater operational comfort level for neurosurgeons while they are performing 2D or 3D motor tasks. For performing complex 3D motor tasks, 3D exoscopes offer selective advantages in dexterity, performance, and operational comfort level over 2D exoscopes. The relative impact of visualization aids on surgical proficiency gradually weakens as the participants’ residency duration increases
Impact of frailty on surgery for glioblastoma: a critical evaluation of patient outcomes and caregivers’ perceptions in a developing country
No full textOBJECTIVE
The authors aimed to evaluate the impact of age and frailty on the surgical outcomes of patients with glioblastoma (GBM) and to assess caregivers’ perceptions regarding postdischarge care and challenges faced in the developing country of India.
METHODS
This was a retrospective study of patients with histopathologically proven GBM from 2009 to 2018. Data regarding the clinical and radiological characteristics as well as surgical outcomes were collected from the institute’s electronic database. Taking Indian demographics into account, the authors used the cutoff age of 60 years to define patients as elderly. Frailty was estimated using the 11-point modified frailty index (mFI-11). Patients were divided into three groups: robust, with an mFI score of 0; moderately frail, with an mFI score of 1 or 2; and severely frail, with an mFI score ≥ 3. A questionnaire-based survey was done to assess caregivers’ perceptions about postdischarge care.
RESULTS
Of the 276 patients, there were 93 (33.7%) elderly patients and 183 (66.3%) young or middle-aged patients. The proportion of severely frail patients was significantly more in the elderly group (38.7%) than in the young or middle-aged group (28.4%) (p < 0.001). The authors performed univariate and multivariate analysis of associations of different short-term outcomes with age, sex, frailty, and Charlson Comorbidity Index. On the multivariate analysis, only frailty was found to be a significant predictor for in-hospital mortality, postoperative complications, and length of hospital and ICU stay (p < 0.001). On Cox regression analysis, the severely frail group was found to have a significantly lower overall survival rate compared with the moderately frail (p = 0.001) and robust groups (p < 0.001). With the increase in frailty, there was a concomitant increase in the requirement for readmissions (p = 0.003), postdischarge specialist care (p = 0.001), and help from extrafamilial sources (p < 0.001). Greater dissatisfaction with psychosocial and financial support among the caregivers of severely frail patients was seen as they found themselves ill-equipped to provide postdischarge care at home (p < 0.001).
CONCLUSIONS
Frailty is a better predictor of poorer surgical outcomes than chronological age in terms of duration of hospital and ICU stay, postoperative complications, and in-hospital mortality. It also adds to the psychosocial and financial burdens of the caregivers, making postdischarge care challenging
Game Level Blending using a Learned Level Representation
No full textGame level blending via machine learning, the process of combining features
of game levels to create unique and novel game levels using Procedural Content
Generation via Machine Learning (PCGML) techniques, has gained increasing
popularity in recent years. However, many existing techniques rely on
human-annotated level representations, which limits game level blending to a
limited number of annotated games. Even with annotated games, researchers often
need to author an additional shared representation to make blending possible.
In this paper, we present a novel approach to game level blending that employs
Clustering-based Tile Embeddings (CTE), a learned level representation
technique that can serve as a level representation for unannotated games and a
unified level representation across games without the need for human
annotation. CTE represents game level tiles as a continuous vector
representation, unifying their visual, contextual, and behavioral information.
We apply this approach to two classic Nintendo games, Lode Runner and The
Legend of Zelda. We run an evaluation comparing the CTE representation to a
common, human-annotated representation in the blending task and find that CTE
has comparable or better performance without the need for human annotation.Comment: 8 pages, 3 figure
Interplay of Dynamic Extension Reserve and T1 Slope in Determining the Loss of Cervical Lordosis Following Laminoplasty: A Novel Classification System
No full textBackground
Laminoplasty causes destruction of the posterior musculoligamentous complex, which may result in cervical kyphosis, or more commonly loss of cervical lordosis (LOCL). In this study, we evaluated the role of various preoperative radiologic parameters in predicting not only the LOCL/kyphosis but also the functional outcomes in the form of change in Oswestry Disability Index (ODI) score following laminoplasty.
Methods
Patients were evaluated both clinically and radiologically with dynamic cervical spine radiograph, noncontrast-enhanced computed tomography, and magnetic resonance imaging of the cervical spine preoperatively as well as at 1 year follow-up.
Results
One hundred twenty-one patients who underwent laminoplasty for cervical spondylotic myelopathy/ossified posterior longitudinal ligament from 2011 to 2018 at our center were included in final analysis. In multivariate analysis, preoperative Cobb angle (P = 0.001), T1 slope (TIS; P = 0.001), and dynamic extension reserve (P < 0.001) were found to have an independent effect on LOCL. The receiver operating characteristic curve using the regression model significantly predicted LOCL >10° with an area under the curve of 88.3% (P < 0.001). Similarly, preoperative T1S (P = 0.036) and SVA (P < 0.001) were found to be independent predictors of significant improvement in ODI after laminoplasty. The receiver operating characteristic curve using the regression model significantly predicted change in ODI with an area under the curve of 83.7% (P < 0.001). Based on these findings, classification and scoring systems with good accuracy have been proposed for prediction of LOCL and improvement in ODI.
Conclusions
We have found that the chances of significant LOCL is determined by an interplay of preoperative Cobb angle, T1S, and dynamic extension reserve
Frailty and Neutrophil Lymphocyte Ratio as Predictors of Mortality in Patients with Catheter-Associated Urinary Tract Infections or Central Line–Associated Bloodstream Infections in the Neurosurgical Intensive Care Unit: Insights from a Retrospective Study in a Developing Country
No full textObjective
We aim to evaluate the role of frailty and inflammatory markers in predicting the short-term outcomes after catheter-associated urinary tract infections (CAUTI) and central line–associated bloodstream infections (CLABSI).
Methods
Data regarding the patients’ characteristics, isolates on CAUTI and CLABSI, antibiotic susceptibility, frailty (11-point Modified Frailty Index), and inflammatory markers were retrospectively collected. Their impact on the short-term outcomes was assessed using regression modeling response.
Results
One hundred and one patients with CAUTI (n = 71) and CLABSI (n = 30) between January 2018 and December 2019 were included in this study. The pooled incidence rates for CAUTI were 5.50 and for CLABSI 3.58 episodes/1000 catheter-days. We observed 74.7% drug resistance in our CAUTI isolates and 93.3% in CLABSI. In the multivariate analysis, frailty (P = 0.006), neutrophil/lymphocyte ratio (NLR) (P = 0.007) and the presence of sepsis (P = 0.029) were found to be significant predictors of in-hospital mortality in CAUTI. In patients with CLABSI, frailty (P = 0.029) and NLR (P = 0.029) were found significant and along with sepsis (P = 0.069) resulted in a regression model with good accuracy in predicting mortality. The receiver operating characteristic curve showed that 11-point Modified Frailty Index and NLR as well as the regression model significantly predicted mortality with an area under the curve of 86.1%, 81.4%, and 95.4%, respectively, in CAUTI, and 70.9%, 77.8%, and 95.2%, respectively, in CLABSI
MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks
No full textThis MOCAS is a multimodal dataset dedicated for human cognitive workload (CWL) assessment. In contrast to existing datasets based on virtual game stimuli, the data in MOCAS was collected from realistic closed-circuit television (CCTV) monitoring tasks, increasing its applicability for real-world scenarios. To build MOCAS, two off-the-shelf wearable sensors and one webcam were utilized to collect physiological signals and behavioral features from 21 human subjects. After each task, participants reported their CWL by completing the NASA-Task Load Index (NASA-TLX) and Instantaneous Self Assessment (ISA). Personal background (e.g., personality and prior experience) was surveyed using demographic and Big Five Factor personality questionnaires, and two domains of subjective emotion information (i.e., arousal and valence) were obtained from the Self-Assessment Manikin, which could serve as potential indicators for improving CWL recognition performance. Technical validation was conducted to demonstrate that target CWL levels were elicited during simultaneous CCTV monitoring tasks; its results support the high quality of the collected multimodal signals.This material is based upon work supported by the National Science Foundation under Grant No. IIS-1846221. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation
