Performance of case-based reasoning retrieval using classification based on associations versus Jcolibri and FreeCBR : a further validation study

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR

Outcome measures in neurosurgery: is a unified approach better? A literature review

Background: Accurate assessment and evaluation of health interventions are crucial to evidence-based care. The use of outcome measures in neurosurgery grew with the introduction of the Glasgow Coma Scale. Since then, various outcome measures have appeared, some of which are disease-specific and others more generally. This article aims to address the most widely used outcome measures in three major neurosurgery subspecialties, "vascular, traumatic, and oncologic," focusing on the potential, advantages, and drawbacks of a unified approach to these outcome measures. Methods: A literature review search was conducted by using PubMed MEDLINE and Google scholar Databases. Data for the three most common outcome measures, The Modified Rankin Scale (mRS), The Glasgow Outcome Scale (GOS), and The Karnofsky Performance Scale (KPS), were extracted and analyzed. Results: The original objective of establishing a standardized, common language for the accurate categorization, quantification, and evaluation of patients' outcomes has been eroded. The KPS, in particular, may provide a common ground for initiating a unified approach to outcome measures. With clinical testing and modification, it may offer a simple, internationally standardized approach to outcome measures in neurosurgery and elsewhere. Based on our analysis, Karnofsky's Performance Scale may provide a basis of reaching a unified global outcome measure. Conclusion: Outcome measures in neurosurgery, including mRS, GOS, and KPS, are widely utilized assessment tools for patients' outcomes in various neurosurgical specialties. A unified global measure may offer solutions with ease of use and application; however, there are limitations.</p

Early Effects of COVID-19 Pandemic on Neurosurgical Training in the United States: A Case Volume Analysis of 8 Programs

To determine the impact of the 2019 novel coronavirus disease (COVID-19) pandemic on operative case volume in 8 U.S. neurosurgical residency training programs in early 2020 and to survey these programs regarding training activities during this period. A retrospective review was conducted of monthly operative case volumes and types for 8 residency programs for 2019 and January through April 2020. Cases were grouped as elective cranial, elective spine, and nonelective emergent cases. Programs were surveyed regarding residents' perceptions of the impact of COVID-19 on surgical training, didactics, and research participation. Data were analyzed for individual programs and pooled across programs. Across programs, the 2019 monthly mean ± SD case volume was 211 ± 82; 2020 mean ± SD case volumes for January, February, March, and April were 228 ± 93, 214 ± 84, 180 ± 73, and 107 ± 45. Compared with 2019, March and April 2020 mean cases declined 15% (P = 0.003) and 49% (P = 0.002), respectively. COVID-19 affected surgical case volume for all programs; 75% reported didactics negatively affected, and 90% reported COVID-19 resulted in increased research time. Several neurosurgery residents required COVID-19 testing; however, to our knowledge, only 1 resident from the participating programs tested positive. This study documents a significant reduction in operative volume in 8 neurosurgery residency training programs in early 2020. During this time, neurosurgery residents engaged in online didactics and research-related activities, reporting increased research productivity. Residency programs should collect data to determine the educational impact of the COVID-19 pandemic on residents' operative case volumes, identify deficiencies, and develop plans to mitigate any effects

Oil palm (Elaeis guineensis) biomass in Malaysia: The present and future prospects

Oil palm industry is the largest contributor of biomass in Malaysia. Oil palm biomass are constantly generated in large quantities annually with a small fraction being converted into value added product while a large percentage are left underutilized. Several researchers have reported the various technologies available for the conversion of oil palm biomass into useful bio-products, including bio-fuel, biogas, bio-fertilizers, bio-composite and briquettes. In general, these technologies are either underutilized or inadequate for full conversion of these abundantly available biomass, hence, there is an urgent need for upgrading of such technologies. This review article highlights the availability of oil palm biomass in Malaysia, the chemical compositions, as well as a brief description of current technologies for converting oil palm biomass into value added products. The review also outlines a summary of the various products obtained from oil palm biomass. Steps to achieve maximum utilization of biomass from oil palm industry are also proposed