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BACKGROUND: Grading the illness using clinical parameters is essential for the daily progress of inpatients. Existing systems do not incorporate these parameters holistically. The study was designed to internally validate the illness wellness scale, based upon clinical assessment of the patients requiring surgical care, for their risk stratification and uniformity of communication between health care providers. METHODS: Prospective observational study conducted at a tertiary care hospital. An expert panel devised the scale, and it was modified after feedback from 100 health care providers. A total of 210 patients (150 for internal validation and 60 for inter-observer variability) who required care under the department of surgical disciplines were enrolled. This included patients presenting to surgery OPD, admitted to COVID/non-COVID surgical wards and ICUs, aged ≥16 years. RESULTS: The response rate of the final illness wellness scale was 95% with 86% positive feedback and a mean of 1.7 on the Likert scale for ease of use (one being very easy and five being difficult). It showed excellent consistency and minimal inter-observer variability with the intra-class correlation coefficient (ICC) above 0.9. In the internal validation cohort (n = 150), univariate and multivariable analysis of factors affecting mortality revealed that categorical risk stratification, age ≥ 60 years, presence or absence of co-morbidities especially hypertension and chronic kidney disease significantly affect mortality. CONCLUSIONS: The Illness wellness scale is an effective tool for uniformly communicating between health care professionals and is also a strong predictor of risk stratification and mortality in patients requiring surgical care.
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Contemporary museums serve for education, research, and enjoyment, and their primary objectives are collection, documentation, and exhibition of cultural heritage. Thus, museum buildings have become common spaces of urban life through these new functions and activities rather than isolated exhibition spaces. They define inclusive complexes with educational research and social and public areas, establishing more effective interaction with society. These activities can be performed competently and appropriately depending on the multi-functional spatial configuration to provide urban experiences with participation and inclusiveness. In this context, this paper aims to study the level of inclusiveness of the first contemporary art museum of Istanbul-Istanbul Modern Museum-through detailed examinations of the architectural configuration with grading criteria based on spatial relations in terms of various facilities of the museum. The story of Istanbul Modern started by re-functioning the old Bosphorus dock's warehouses in 2004. The museum temporarily moved to another historic building in 2018, where it has also experienced new COVID19 pandemic conditions. Istanbul Modern is still in a process of moving back to its former location into a new building designed as a museum by Renzo Piano Building Workshop Architects. Through three phases, inclusivity and participation of buildings will be cross-examined on a developed rating-scale technique based on included sociocultural activities by their spatial sizes and relations through quantitative analysis. This methodology will provide preliminary knowledge for future research on museum architectonics.
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Introduction: Colorectal Cancer (CRC) is on the rise, prompting the need for earlier screening in the United States (U.S.) population. The American Cancer Society now recommends screening for CRC in patients with average risk at the age of 45. Further complicating this picture, the COVID-19 pandemic has disrupted the routine screening process for CRC, which we hypothesize has impacted the stage at which CRC is detected. We sought to determine the extent to which the COVID-19 pandemic has affected colorectal cancer diagnosis trends at a large urban community hospital. Method(s): We performed a retrospective analysis of patients, comparing two time periods: pre-pandemic (1/1/2019-1/31/2020) and during COVID pandemic (2/1/2020-9/29/21). Data was extracted from the electronic medical record (EMR) to compile a database of patients diagnosed with CRC during these time periods. Patients included in this study had a new diagnosis of colorectal cancer and either followed with colorectal specialists at the hospital or had undergone tissue biopsy analysis by the Department of Pathology. The primary outcome was determining the stage at which CRC was detected and the modality utilized for CRC screening in that patient. Additional variables collected were as follows: age, pathological findings (grade, presence of tumor mutations, or microsatellite instability), gender, race, and insurance. Result(s): Data was collected from a total of 380 patients, which included 190 patients diagnosed with CRC within the timeframe defined as pre-pandemic and 190 diagnosed with CRC within the timeframe defined as during the pandemic. CRC diagnosis was analyzed in terms of TNM stage at time of diagnosis (Stages 0 through IV). Stage III and IV were grouped together and categorized as a late-stage diagnosis, whereas Stages 0, I, and II were grouped together and categorized as an early-stage diagnosis. Late-stage diagnosis was found in 34.7% (66/190) of patients in the pre-pandemic group. In comparison, late-stage diagnosis was found in 46.3% (88/190) of patients in the during pandemic group. Conclusion(s): Our results suggest that the COVID-19 pandemic did produce delays in care and work-up for CRC. We believe this is why CRC stage at the time of initial diagnosis was later for patients diagnosed during the pandemic than for patients diagnosed prior to the pandemic. In the future, we hope to evaluate if the impact of COVID-19 is reflected in tumor grade and genetic mutations at the time of diagnosis, and determine race and gender disparities.
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To help students cope with the challenges of the COVID-19 pandemic, higher education institutions offered students flexible grading policies that blended traditional letter grades with alternative grading options such as the pass-fail or credit-no credit options. This study conducted an in-depth analysis of the flexible grading policy at a medium-sized university in the USA. We studied the differential selection of flexible grading options by course characteristics and students' sociodemographics and academic profiles between Spring 2020 and Spring 2021. We also examined the impacts of the policy on sequential courses. Our analysis utilized administrative and transcript data for undergraduate students at the study institution and employed a combination of descriptive statistics and regression models. The analysis revealed that the flexible grading policy was utilized differently depending on course characteristics, with core courses and subjects like mathematics, chemistry, and economics having higher rates of usage. Additionally, sociodemographic and academic profile factors led to varying degrees of utilization, with males, urban students, freshmen, and non-STEM majors using the policy more frequently. Furthermore, the analysis suggested that the policy may have disadvantaged some students as they struggled in subsequent courses after using the pass option. Several implications and directions for future research are discussed.
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Mucormycosis is an opportunistic fungal infection. India faced an unprecedented increase in patients with post coronavirus disease 2019 (COVID-19) associated rhino-orbito-cerebral mucormycosis (ROCM). This study proposes a grading system which correlates the extent of the disease with the management plan. An observational study was conducted January 2021-June 2021. We identified 65 patients. Eleven patients had mild disease, 27 patients had moderate, 16 patients were severe and 11 patients were graded as very severe. The management was planned based on this grading system. Early diagnosis, aggressive surgical debridement and antifungal drug therapy is the key to improve survival in ROCM. Procedures such as endoscopic orbital clearance, sublabial maxillectomy, and modified endoscopic Denkers (MED) approach facilitate access and surgical debridement. The new grading system proposed assists in planning the approach and extent of surgical debridement.
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During the Covid-19 lockdowns, e-learning and e-assessment became immensely popular worldwide. Exam Wizard is a web-based online e-assessment platform which provides a variety of features including question pool creation, automatic grading, automatic resumption, reusability, simplicity, exam monitoring and scheduling, weighted questions, a count-down timer, and automatic generation of statistics. Exam Wizard supports three kinds of users: administrators, instructors and students. This paper describes some new features of Exam Wizard, as well as the responsibilities and the User Interfaces (UI) of each user role. In addition, this paper describes the instructor's experience from the use of Exam Wizard in pilot tests and midterm exams of technical courses offered by a higher education institution. The instructor found the tool useful because it produces immediate results, saving time and effort;when the instructor's time is limited or in the case of large classes, e-assessment is the only viable option. During the evaluation of Exam Wizard the students appreciated the fact that they received immediate feedback, and the instructor happily stated that as long as there are questions banks available, it is a matter of minutes to create a new exam. © 2022 ACM.
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Dermatological emergency is defined as any urgent/immediate care. Dermatological conditions compromise about 5-8% of all cases presenting to the emergency department. A grading system can help dermatologist's and allied medical personnel to triage a patient accordingly. Currently no severity grading for dermatological emergencies is available. All patients seen in OPD for dermatological consultations requiring urgent interventions were included. Detailed history and clinical examination were done. Patients were assessed according to the onset, symptoms, distribution, examination, body surface area percentage and mucosal involvement. The severity was graded separately based on comorbidities and systemic involvement. Grade I was no comorbidity or systemic involvement. Grade II was 1 comorbidity or systemic involvement. Grade III was 2 comorbidities or systemic involvement. Grade IV was > 2 comorbidities or multiorgan involvement. Interesting emergency cases observed in Covid period were noted. There were 202 cases, the most common age group was 19-64 (69.8%). Male (49%) and females (51%) had equal preponderance. Most common emergency was acute urticaria with or without angioedema (25.24%). There were 113 (55.94%) inpatients and 89 (44.05%) were outpatients. Acute on chronic onset (34.5%), pain (41.6%), vesicles (30.1%), erosion (23.9%), ulcers (9.7%) and more than 50% body surface area involvement (64.6%) were seen more in admitted cases. Grade I was most common for both comorbidities and systemic involvement. However, grades II, III and IV were higher in admitted cases for both grading systems. The presence of comorbidities and systemic involvement increases the severity of dermatological emergency. Six patients had relapse. Seven patients had methotrexate toxicity. The proposed grading system based on comorbidities and systemic involvement helps to assess the severity of dermatological emergencies.
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The requirement for remote examination had emerged along with remote learning during the COVID-19 pandemic as the unprecedented situation had brought the world to halt. The pandemic had forced many educational institutions to move towards the online mode of assessment to assess the caliber of the students. This paper focuses on the ways that an online examination system can be prepared and can be used for conducting exams remotely in a secure way. It also emphasizes on various test cases that are essential for an efficient and useful examination system that can benefit both students and faculty by saving them time and effort. Due to the challenges in the existing mode of online assessment such as the use of digital forms that are usually used for conducting surveys, scanning and uploading answer sheets using phone with poor camera quality, the problem of engaging in the different kinds of misconduct, it was important to understand the user requirements at an examiner and examinee level and prepare a web application that addresses them and makes it convenient to conduct and attempt. We propose different methodologies that can be implemented in a Python based web application with the help of JavaScript such as switching the browser window to full-screen in order to restrict access to other applications, limited exits from full-screen, easy management of examiner and candidate data along with visualization of exam data that help to better understand and draw quick conclusions at the time of exam. It is also focused on the continuously evolving distance education system and finding the best software solution possible for online examinations. Additionally, an automated grading system may help to reduce human error and declare results easily reducing fatigue. © 2022 IEEE.
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Students' performance can be assessed based on grading the answers written by the students during their examination. Currently, students are assessed manually by the teachers. This is a cumbersome task due to an increase in the student-teacher ratio. Moreover, due to coronavirus disease (COVID-19) pandemic, most of the educational institutions have adopted online teaching and assessment. To measure the learning ability of a student, we need to assess them. The current grading system works well for multiple choice questions, but there is no grading system for evaluating the essays. In this paper, we studied different machine learning and natural language processing techniques for automated essay scoring/grading (AES/G). Data imbalance is an issue which creates the problem in predicting the essay score due to uneven distribution of essay scores in the training data. We handled this issue using random over sampling technique which generates even distribution of essay scores. Also, we built a web application using flask and deployed the machine learning models. Subsequently, all the models have been evaluated using accuracy, precision, recall, and F1-score. It is found that random forest algorithm outperformed the other algorithms with an accuracy of 97.67%, precision of 97.62%, recall of 97.67%, and F1-score of 97.58%. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
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The assessment of students' performances in Higher Education is one of the essential components of teaching activities. Open-ended tasks allow a more in-depth assessment of students' learning levels, but their evaluation and grading are time-consuming and prone to subjective bias. Since the Covid-19 pandemic, most traditional Higher Education courses converted to online courses;automatic grading and feedback tools and methods (AGFTM) have become critical components of online learning systems, especially with regards to short answers and essays assessment. This work frames the recent advancement in AGFTM through a systematic mapping of the research field and a literature review. This analysis gives an overview of the trends, specific goals, methods, quality of proposals, challenges and limitations in this research area. The results indicate that it is a growing research area, with a large set of techniques involved, but still not mature, where practical implementations have yet to come. © 2023 Elsevier Ltd
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In 1984, the film "The Terminator” predicted that a hostile Artificial Intelligence (AI) will threaten to extinguish humankind by 2029. Even though the real present is quite far from this post-apocalyptic scenario where AI rebels against its creator, a growing concern about the lack of ethical considerations in the use of AI is rapidly spreading, leading to the current "ethics crisis”. The lack of clear regulations is even more alarming considering that AI is becoming an integral part of new educational platforms. This follows the wave of digital transformation mainly induced by the Fourth Industrial Revolution, with advances in digitalization strategies, and the COVID-19 crisis, which forced education institutions worldwide to switch to e-learning. The appeal of AI is its potential to answer the needs of both educators and learners. For example, it can provide help grading assignments, enable tutoring opportunities, develop smart content, personalize and ultimately boost on-line learning. Although the "AI revolution” has great potential to improve and boost digital education, there are no clear regulations in place to ensure an ethical and fair use of AI. Therefore, this work aims to provide a comprehensive overview of the current concerns regarding fairness, accountability, transparency and ethics in AI applied to education, with specific focus on virtual laboratories. The main aspects that this work aims to discuss, and provide possible suggestions for, are: (i) ethical concerns, fairness, bias, equity, and inclusion;(ii) data transparency and digital rights, including data availability, collection, and protection;and, (iii) collaborative approach between disciplines. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings. All rights reserved.
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Background: The COVID-19 pandemic had a significant impact on the healthcare system globally, including oncology. Which, in turn, led to significant delays in diagnostic and therapeutic procedures. This work aims to evaluate COVID-19 impact on the treatment of bone sarcoma in adult patients based on experience in a single, high-volume institution. Method(s): We have analyzed the early local outcomes (i.e., the possibility of limb-sparing surgery) in all patients with primary bone tumours treated between 2016-01-28 and 2022-11-07 in Polish main sarcoma reference center. Patients treated in the 2016-2019 period were labelled as a "pre-pandemic" group, and patients treated in the 2020-2022 - "pandemic". Mann-Whitney U and Chi-square tests were used in the statistical analysis. Result(s): There were 302 eligible patients identified. The group characteristics are presented in the table. There were no differences in patient-related variables and histological subtypes of tumours between the two groups. The tumour size did not differ (p = 0.053), when all tumour grades were considered, but high-grade tumours were larger in the "pandemic" group (p = 0.034). This was reflected in the percentage of limb-sparing surgeries which dropped from 83.3% to 68.2% ("pre-pandemic" vs "pandemic", p = 0.004). This difference was even more evident in the case of high-grade tumors - 78% vs. 54%, respectively (p = 0.001). [Formula presented] Conclusion(s): To our knowledge, this is the first report of the long-lasting detrimental impact of the COVID-19 pandemic on oncologic treatment outcomes in adult patients with primary malignant bone tumors. Legal entity responsible for the study: The authors. Funding(s): Has not received any funding. Disclosure: All authors have declared no conflicts of interest.Copyright © 2023 European Society for Medical Oncology
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The pandemic brought a massive shift in traditional education strategies. Educational literature is focusing on case studies for online-learning platforms. This research aims to break down the adaptations in teaching styles and curriculums across different countries due to the worldwide shift towards newer technology and learning mediums to facilitate students. Analyzing aspects like motivation, access to network services, grading schemes, teaching styles, and curriculum changes, this research utilizes a cross-country comparison through existing local research in various parts of the globe to summarize the changes that educational institutions in higher education have incorporated into their syllabi and teaching methods. A survey was carried out at Al Ain university consisting of 174 students and 31 faculty members who rated their motivation levels and satisfaction with online learning vs. traditional methods. This survey revealed various answers showcasing the need for institutional training, student-centered curriculums, and syllabi objectives that need to be predetermined and implemented to foster students' well-being and interest in the subject matter rather than knowledge acquisition. Moreover, through analyzing different countries' teaching methodologies, we found that developing key competencies and curriculum objectives with different options and mediums available to students is vital to establish agency for students' well-being. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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This paper presents our solution for the 2nd COVID-19 Severity Detection Competition. This task aims to distinguish the Mild, Moderate, Severe, and Critical grades in COVID-19 chest CT images. In our approach, we devise a novel infection-aware 3D Contrastive Mixup Classification network for severity grading. Specifically, we train two segmentation networks to first extract the lung region and then the inner lesion region. The lesion segmentation mask serves as complementary information for the original CT slices. To relieve the issue of imbalanced data distribution, we further improve the advanced Contrastive Mixup Classification network by weighted cross-entropy loss. On the COVID-19 severity detection leaderboard, our approach won the first place with a Macro F1 Score of 51.76%. It significantly outperforms the baseline method by over 11.46%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Previous research has shown that a semester-long multicultural psychology course can effectively increase students' cultural competence-related attitudes when students complete the class in-person and online. Cultural competence refers to the knowledge, awareness, and skills required to appreciate, recognize, and effectively work with members of other cultural groups. This dissertation examined several components of a multicultural psychology course: ethical grading, skill development, and intergroup contact. The first paper discussed techniques used to minimize grading bias and examined whether cultural competence shifts impacted grading. Students' cultural competence scores did not relate to or predict their grades in the course, which supported the notion instructors can grade fairly and objectively regardless of students' attitudes and values. The second paper highlighted the importance of social justice competence in addition to cultural competence, as well as the importance of targeting skill development in addition to knowledge and awareness. This study investigated the impact of adding a skills-focused Difficult Dialogues group assignment to the course on students' shifts in cultural competence-related attitudes and social justice orientation and also discussed of implementation considerations for instructors. Results suggested that the Difficult Dialogues project had a particular impact on improving students' social justice behavioral intentions. The third paper focused on the impact of intergroup contact with diverse others. The multicultural psychology course typically requires direct contact by attending at least three cultural events every semester. However, due to the COVID-19 pandemic, this requirement was shifted to indirect contact activities. This study examined differential shifts on students' cultural competence-related attitudes in sections where students were required to engage in direct intergroup contact versus students who were allowed to engage in indirect intergroup contact due to taking the course during the COVID-19 pandemic. Results suggest that indirect contact contributed to positive shifts in cultural competence equally as well as direct intergroup contact. These studies advance the evidence-based teaching of multicultural psychology by empirically examining specific course components. The manuscripts provide useful information for educators, administrators, advocates, and policymakers about the impact of multicultural education, the efficacy of cultural competence training, and feasibility of ethical implementation in the classroom. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
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Chest X-rays (CXR) are the most commonly used imaging methodology in radiology to diagnose pulmonary diseases with close to 2 billion CXRs taken every year. The recent upsurge of COVID-19 and its variants accompanied by pneumonia and tuberculosis can be fatal in some cases and lives could be saved through early detection and appropriate intervention for the advanced cases. Thus CXRs can be used for an automated severity grading of pulmonary diseases that can aid radiologists in making better and informed diagnoses. In this article, we propose a single framework for disease classification and severity scoring produced by segmenting the lungs into six regions. We present a modified progressive learning technique in which the amount of augmentations at each step is capped. Our base network in the framework is first trained using modified progressive learning and can then be tweaked for new data sets. Furthermore, the segmentation task makes use of an attention map generated within and by the network itself. This attention mechanism allows to achieve segmentation results that are on par with networks having an order of magnitude or more parameters. We also propose severity score grading for 4 thoracic diseases that can provide a single-digit score corresponding to the spread of opacity in different lung segments with the help of radiologists. The proposed framework is evaluated using the BRAX data set for segmentation and classification into six classes with severity grading for a subset of the classes. On the BRAX validation data set, we achieve F1 scores of 0.924 and 0.939 without and with fine-tuning, respectively. A mean matching score of 80.8% is obtained for severity score grading while an average area under receiver operating characteristic curve of 0.88 is achieved for classification.
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Since the outburst of the Covid-19 pandemic it is very common that students widely use videos in higher education. In an introductory material science course for mechanical and automotive engineers lecture videos have successfully been implemented in inverted classroom teaching scenarios at HTW Berlin. Inspired by former students a set of lecture videos is produced during a one term project each semester. This peer-to-peer approach is an important aspect because students' needs and their perspective on teaching material is directly included in the videos. In this study five different lecture film types were investigated with regard to students' performance and micro grading comprising of: swipe technique, stop motion, power point animation, hand drawn and video scribe. In general, students' performance was found to be more successful before the pandemic. However, the type of lecture film types could not directly be related to student grades but are rated successful regarding concentration, responsibility and attentiveness as well as depth of discussions during class. © 2022 IEEE.
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While some tertiary mathematics educators approximated the familiar invigilated, closed-book assessment regime in the online environment forced upon us all by a pandemic, others either by choice or necessity needed to devise a new way to assess their students' learning. This Classroom Note both synthesizes advice from the literature about what might comprise 'internet resistant' question design and provides practical, specific examples to demonstrate how such advice can be put into everyday practice. The examples are annotated, and the potential long-term utility of such question design is discussed, whatever the future of assessment may be.
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The research and data aim to (a) examine instructors' evaluation of Microsoft Teams as reflected in their teaching at the Public Authority for Applied Education and Training (PAAET) and (b) identify significant correlation between three determinants of the Technology Acceptance Model: perceived usefulness (PU), perceived ease of use (PEOU), and attitudes towards use (ATU). The researchers used a self-report survey answered by 230 instructors from multiple departments at the College of Basic Education. Several statistical tools examined mean differences. The research found that the instructors at PAAET highly rate Microsoft Teams. Perceived usefulness directly affected attitudes towards use while perceived ease of use (PEOU) indirectly affected attitudes towards use.