Multistage Classification and Segmentation of Brain MR Image using Modified Soft Computing Techniques

Recent studies indicate that brain tumor is one of the major causes of human casualties. Timely and accurate diagnosis of this life taking disease could reduce the casualty rate and extend the life of a person. In this research paper, techniques for brain tumor detection from MR Images with malignancy using modified soft computing approaches are presented and analyzed. An automated tumor detection system using artificial neural network (ANN) is proposed to classify the images as any of the four classes: Glioblastoma multiforme, Meningioma, secondary tumor-Metastasis and No Tumor. The classified image undergoes a segmentation process that predicts the size of the tumor in terms of pixels. Traditionally, conventional self-organizing map (CSOM) and Conventional back Propagation network (CBPN) are used for classification and segmentation respectively. However, these methods provide less accurate results in addition to high computational complexity. Moreover, due to unstable target weights, the number of iterations is large. These drawbacks are overcome in the proposed technique by developing a modified SOM (MSOM) for classification of images and modified BPN (MBPN) for segmentation. Simulated results show that the proposed modifications minimize the computational complexity without compromising on the accuracy. It is shown that MSOM increases the accuracy of classification by 10% compared to its conventional counterpart. Similarly segmentation accuracy is improved by 8% using MBPN

Obstetric anal sphincter injury: a systematic review of information available on the internet.

OBJECTIVE: There is no systematic evaluation of online health information pertaining to obstetric anal sphincter injury. Therefore, we evaluated the accuracy, credibility, reliability, and readability of online information concerning obstetric anal sphincter injury. MATERIALS AND METHODS: Multiple search engines were searched. The first 30 webpages were identified for each keyword and considered eligible if they provided information regarding obstetric anal sphincter injury. Eligible webpages were assessed by two independent researchers for accuracy (prioritised criteria based upon the RCOG Third and Fourth Degree Tear guideline); credibility; reliability; and readability. RESULTS: Fifty-eight webpages were included. Seventeen webpages (30%) had obtained Health On the Net certification, or Information Standard approval and performed better than those without such approvals (p = 0.039). The best overall performing website was http://www.pat.nhs.uk (score of 146.7). A single webpage (1%) fulfilled the entire criteria for accuracy with a score of 18: www.tamesidehospital.nhs.uk . Twenty-nine webpages (50%) were assessed as credible (scores ≥7). A single webpage achieved a maximum credibility score of 10: www.meht.nhs.uk . Over a third (21 out of 58) were rated as poor or very poor. The highest scoring webpage was http://www.royalsurrey.nhs.uk (score 62). No webpage met the recommended Flesch Reading Ease Score above 70. The intra-class coefficient between researchers was 0.98 (95% CI 0.96-0.99) and 0.94 (95% CI 0.89-0.96) for accuracy and reliability assessments. CONCLUSION: Online information concerning obstetric anal sphincter injury often uses language that is inappropriate for a lay audience and lacks sufficient accuracy, credibility, and reliability

Updated consensus guidelines on the management of Phelan–McDermid syndrome

Phelan–McDermid syndrome (PMS) is a genetic condition caused by SHANK3 haploinsufficiency and characterized by a wide range of neurodevelopmental and systemic manifestations. The first practice parameters for assessment and monitoring in individuals with PMS were published in 2014; recently, knowledge about PMS has grown significantly based on data from longitudinal phenotyping studies and large-scale genotype–phenotype investigations. The objective of these updated clinical management guidelines was to: (1) reflect the latest in knowledge in PMS and (2) provide guidance for clinicians, researchers, and the general community. A taskforce was established with clinical experts in PMS and representatives from the parent community. Experts joined subgroups based on their areas of specialty, including genetics, neurology, neurodevelopment, gastroenterology, primary care, physiatry, nephrology, endocrinology, cardiology, gynecology, and dentistry. Taskforce members convened regularly between 2021 and 2022 and produced specialty-specific guidelines based on iterative feedback and discussion. Taskforce leaders then established consensus within their respective specialty group and harmonized the guidelines. The knowledge gained over the past decade allows for improved guidelines to assess and monitor individuals with PMS. Since there is limited evidence specific to PMS, intervention mostly follows general guidelines for treating individuals with developmental disorders. Significant evidence has been amassed to guide the management of comorbid neuropsychiatric conditions in PMS, albeit mainly from caregiver report and the experience of clinical experts. These updated consensus guidelines on the management of PMS represent an advance for the field and will improve care in the community. Several areas for future research are also highlighted and will contribute to subsequent updates with more refined and specific recommendations as new knowledge accumulates

POWDERDAY: Dust Radiative Transfer for Galaxy Simulations

We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, allowing significant flexibility in the assumed stellar physics and nebular line emission. The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 Å–1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. We demonstrate the capabilities of the code via three applications: a model for the star formation rate–infrared luminosity relation in galaxies (including the impact of AGNs), the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs, and the impact of galaxy inclination angle on dust attenuation laws