Educational Stakeholders’ Independent Evaluation of an Artificial Intelligence-Enabled Adaptive Learning System Using Bayesian Network Predictive Simulations

Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved for large-scale deployment. Beyond simply believing in the information provided by the AI-ALS supplier, there arises a need for educational stakeholders to independently understand the motif of the pedagogical characteristics that underlie the AI-ALS. Laudable efforts were made by researchers to engender frameworks for the evaluation of AI-ALS. Nevertheless, those highly technical techniques often require advanced mathematical knowledge or computer programming skills. There remains a dearth in the extant literature for a more intuitive way for educational stakeholders—rather than computer scientists—to carry out the independent evaluation of an AI-ALS to understand how it could provide opportunities to educe the problem-solving abilities of the students so that they can successfully learn the subject matter. This paper proffers an approach for educational stakeholders to employ Bayesian networks to simulate predictive hypothetical scenarios with controllable parameters to better inform them about the suitability of the AI-ALS for the students.

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CONTRIBUTION OF DNA COPY-NUMBER VARIATION (CNV) TO CANCER SUSCEPTIBILITY AND LARGE-SCALE GENOME ALTERATIONS IN OSTEOSARCOMA (OS)

Clinical & Investigative Medicine ◽

10.25011/cim.v31i4.4821 ◽

2008 ◽

Vol 31 (4) ◽

pp. 19

Author(s):

I Pasic ◽

A Shlien ◽

A Novokmet ◽

C Zhang ◽

U Tabori ◽

...

Keyword(s):

Genomic Instability ◽

Large Scale ◽

Structural Variation ◽

Age Of Onset ◽

Cancer Susceptibility ◽

Small Sample Size ◽

Snp Array ◽

Tumour Suppressor Gene ◽

Small Sample ◽

International Hapmap Project

Introduction: OS, a common Li-Fraumeni syndrome (LFS)-associated neoplasm, is a common bone malignancy of children and adolescents. Sporadic OS is also characterized by young age of onset and high genomic instability, suggesting a genetic contribution to disease. This study examined the contribution of novel DNA structural variation elements, CNVs, to OS susceptibility. Given our finding of excessive constitutional DNA CNV in LFS patients, which often coincide with cancer-related genes, we hypothesized that constitutional CNV may also provide clues about the aetiology of LFS-related sporadic neoplasms like OS. Methods: CNV in blood DNA of 26 patients with sporadic OS was compared to that of 263 normal control samples from the International HapMap project, as well as 62 local controls. Analysis was performed on DNA hybridized to Affymetrix genome-wide human SNP array 6.0 by Partek Genomic Suite. Results: There was no detectable difference in average number of CNVs, CNV length, and total structural variation (product of average CNV number and length) between individuals with OS and controls. While this data is preliminary (small sample size), it argues against the presence of constitutional genomic instability in individuals with sporadic OS. Conclusion: We found that the majority of tumours from patients with sporadic OS show CN loss at chr3q13.31, raising the possibility that chr3q13.31 may represent a “driver” region in OS aetiology. In at least one OS tumour, which displays CN loss at chr3q13.31, we demonstrate decreased expression of a known tumour suppressor gene located at chr3q13.31. We are investigating the role ofchr3q13.31 in development of OS.

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Review of the Studies in the Use of Biofeedback Therapy in Rehabilitation and Physiatrics of Neurological Patients

Doctor Ru ◽

10.31550/1727-2378-2021-20-9-43-47 ◽

2021 ◽

Vol 20 (9) ◽

pp. 43-47

Author(s):

E.Yu. Mozheyko ◽

◽

O.V. Petryaeva ◽

◽

...

Keyword(s):

Large Scale ◽

Small Sample Size ◽

Small Sample ◽

Healthy Population ◽

Biofeedback Therapy ◽

Level Of Evidence ◽

Double Blind ◽

Key Points ◽

Neurological Patients ◽

Drug Free

Objective of the Review: To collect information, analyse and evaluate previous studies in the use of biofeedback in neurological patients. Key Points. Despite the wide practical application and a lot of available publications, the level of evidence of this method is low because of a small sample size and the challenges with biofeedback mechanism description. A review of various types of biocontrol, its mechanisms and developments shows that drug-free therapy using only patient’s resources (organic, psychological, emotional and volitional) can activate the mechanisms of neuroplasticity, which are poorly studied. Still, it does not prevent from using biocontrol for the therapy of patients and/or prevention of various diseases in healthy population. Conclusion. Biofeedback therapy has proven to be a safe, relatively efficient and easy-to-use method. However, organisation of a large-scale double blind randomized trial is one of the predominant directions in the future. Keywords: biofeedback, biocontrol, neurofeedback, biofeedback therapy.

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Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks

10.1101/115261 ◽

2017 ◽

Author(s):

Stefano Beretta ◽

Mauro Castelli ◽

Ivo Gonçalves ◽

Ivan Merelli ◽

Daniele Ramazzotti

Keyword(s):

Breast Cancer ◽

Graphical Models ◽

Protein Interactions ◽

Large Scale ◽

Small Sample Size ◽

Small Sample ◽

Cancer Data ◽

Correlation Networks ◽

Model Complex ◽

Cancer Networks

AbstractGene and protein networks are very important to model complex large-scale systems in molecular biology. Inferring or reverseengineering such networks can be defined as the process of identifying gene/protein interactions from experimental data through computational analysis. However, this task is typically complicated by the enormously large scale of the unknowns in a rather small sample size. Furthermore, when the goal is to study causal relationships within the network, tools capable of overcoming the limitations of correlation networks are required. In this work, we make use of Bayesian Graphical Models to attach this problem and, specifically, we perform a comparative study of different state-of-the-art heuristics, analyzing their performance in inferring the structure of the Bayesian Network from breast cancer data.

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A Liar’s Epistemology

Qui Parle ◽

10.1215/10418385-8955815 ◽

2021 ◽

Vol 30 (1) ◽

pp. 119-157

Author(s):

Brett Zehner

Keyword(s):

Artificial Intelligence ◽

Intelligent Systems ◽

Large Scale ◽

Computational Models ◽

Nervous Activity ◽

Bad Faith ◽

Computer Scientists ◽

Human Decision ◽

Media Philosophy ◽

Historical Accounts

Abstract This methodologically important essay aims to trace a genealogical account of Herbert Simon’s media philosophy and to contest the histories of artificial intelligence that overlook the organizational capacities of computational models. As Simon’s work demonstrates, humans’ subjection to large-scale organizations and divisions of labor is at the heart of artificial intelligence. As such, questions of procedures are key to understanding the power assumed by institutions wielding artificial intelligence. Most media-historical accounts of the development of contemporary artificial intelligence stem from the work of Warren S. McCulloch and Walter Pitts, especially the 1943 essay “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Yet Simon’s revenge is perhaps that reinforcement learning systems adopt his prescriptive approach to algorithmic procedures. Computer scientists criticized Simon for the performative nature of his artificially intelligent systems, mainly for his positivism, but he defended his positivism based on his belief that symbolic computation could stand in for any reality and in fact shape that reality. Simon was not looking to actually re-create human intelligence; he was using coercion, bad faith, and fraud as tactical weapons in the reordering of human decision-making. Artificial intelligence was the perfect medium for his explorations.

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4375 Developing team science for practical applications of artificial intelligence in health systems to improve value and outcomes: A case study in reducing avoidable emergency department use

Journal of Clinical and Translational Science ◽

10.1017/cts.2020.355 ◽

2020 ◽

Vol 4 (s1) ◽

pp. 117-117

Author(s):

Vladimir G. Manuel ◽

Eran Halperin ◽

Jeffrey Chiang ◽

Kodi Taraszka ◽

Laura Kim ◽

...

Keyword(s):

Artificial Intelligence ◽

Emergency Department ◽

Health Systems ◽

Prediction Models ◽

Interdisciplinary Team ◽

Learning System ◽

Emergency Department Use ◽

System Perspective ◽

System Leaders ◽

Computer Scientists

OBJECTIVES/GOALS: Health care systems are complex, dynamic, and varied. Advances in artificial intelligence (AI) are enabling healthcare systems to use their own data to elicit patterns and design suitable interventions. To realize this potential, computer scientists and clinicians need an effective, practical, and replicable approach to collaboration METHODS/STUDY POPULATION: In this study, computer scientists partnered with clinicians to investigate predictors of avoidable emergency department use. The team sought an approach to computational medicine that could increase the relevance and impact of prediction to solve pressing problems in the health system. The team adopted an emergent architecture that engaged system leaders, computer scientists, data scientists, health services researchers, and practicing clinicians with deep ambulatory and inpatient knowledge to form the initial questions that shaped the prediction model; to understand nuances of coding and recording in source data and the implications for models; and to generate insights for promising points of intervention. The team recorded decisions and challenges as it progressed to analyze its function. RESULTS/ANTICIPATED RESULTS: Most avoidance models focus on a narrow time period around target events, or on high cost patients and events. This interdisciplinary team used their insights into the health system’s workflows and patient population to adopt a longitudinal approach to their prediction models. They used AI to build models of behavior in the system and consider prevention points across clinical units, time, and place. The holistic, systemwide focus enabled the team to generate insights that the system leaders and subsequently specific clinical units could apply to improve value and outcomes. A facilitated team process using learning system and cooperative network principles allowed a large and modular interdisciplinary team to build a transparent AI modeling process that yielded actionable insights into hypercomplex workflows. DISCUSSION/SIGNIFICANCE OF IMPACT: An architecture for involving diverse stakeholders in computational medicine projects can increase the relevance and impact of AI for solving care delivery problems in complex health systems. Translational science and computational medicine programs can foster this type of engagement and encourage a whole system perspective.

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Copy number variation analysis of twin pairs discordant for cleft lip with or without cleft palate

International Journal of Immunopathology and Pharmacology ◽

10.1177/2058738419855873 ◽

2019 ◽

Vol 33 ◽

pp. 205873841985587

Author(s):

Luca Scapoli ◽

Francesco Carinci ◽

Annalisa Palmieri ◽

Francesca Cura ◽

Alessandro Baj ◽

...

Keyword(s):

Cleft Palate ◽

Copy Number ◽

Large Scale ◽

Cleft Lip ◽

Small Sample Size ◽

Copy Number Variants ◽

Monozygotic Twins ◽

Monozygotic Twin ◽

Small Sample ◽

High Level

Non-syndromic cleft lip with or without cleft palate (nsCL/P) is a frequent orofacial malformation. The comparison of concordance rate observed in monozygotic and dizygotic twins supports high level of heritability and a strong genetic component. However, phenotype concordance for orofacial cleft in monozygotic twins is about 50%. The aim of the present investigation was to detect postzygotic events that may account for discordance in monozygotic twins. High-density SNP microarrays hybridization was used to genotype two pairs of monozygotic twins discordant for nsCL/P. Discordant SNP genotypes and copy number variants were analyzed to identify genetic differences responsible of phenotype discrepancy. A number of differences were observed, none involving known nsCL/P candidate genes or genomic regions. Considering the limitation of the study, related to the small sample size and to the large-scale investigation method, the results suggest that the detection of discordant events in other monozygotic twin pairs would be remarkable and warrant further investigations.

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Assessment literacy of foundation phase teachers: An exploratory study

South African Journal of Childhood Education ◽

10.4102/sajce.v5i1.354 ◽

2015 ◽

Vol 5 (1) ◽

pp. 26 ◽

Cited By ~ 7

Author(s):

Anil Kanjee ◽

Jane Mthembu

Keyword(s):

South African ◽

Small Sample Size ◽

Summative Assessment ◽

Small Sample ◽

Assessment Literacy ◽

Learning Needs ◽

National Assessment ◽

Curriculum Policies ◽

Use Of Assessment ◽

The Impact

This study explores foundation phase teachers’ assessment literacy, and their understanding and use of formative and summative assessment. Using questionnaires, observations and interviews, data were obtained from Grade 1, 2 and 3 teachers from a school each in quintile 2, 3 and 5. Teachers from all three schools demonstrated equally low levels of assessment literacy. While understanding of summative assessment was noticeably higher, all teachers demonstrated very poor understanding of formative assessment. Notwithstanding the small sample size, the study highlights the need for professional development programmes to focus on enhancing teachers’ assessment literacy. It also calls for additional research on a conceptualisation of assessment literacy that is relevant to South African teachers, and for determining the impact of concepts and practices advocated in the national assessment and curriculum policies on teachers’ use of assessment to address the learning needs of all learners across schools in the different quintile categories.

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Facebook as a platform for co-creating music festival experiences

International Journal of Event and Festival Management ◽

10.1108/ijefm-02-2016-0012 ◽

2016 ◽

Vol 7 (2) ◽

pp. 84-99 ◽

Cited By ~ 14

Author(s):

Emma Hoksbergen ◽

Andrea Insch

Keyword(s):

Young Adults ◽

Large Scale ◽

Small Sample Size ◽

Small Sample ◽

Survey Method ◽

Future Research ◽

Content Type ◽

Music Festival ◽

Alternative Means ◽

On Line

Purpose The purpose of this paper is to address the need to understand how younger music festival-goers use and engage with a music festival’s Facebook page, and how they perceive this social networking service (SNS) as a potential on-line platform for value co-creation. Design/methodology/approach Face-to-face in-depth interviews were conducted with 16 young adults who attended an annual New Year’s Eve music festival, Rhythm and Vines, in Gisborne, New Zealand. Findings Analysis of the interview data revealed that the majority of participants did not actively engage with this platform and could be categorised as passive viewers or information-seekers. In addition, participants perceived five types of value from using this SNS: functional, social, emotional, interactive and aesthetic value. Even though participants were not segmented due to the small sample size, patterns in their levels of engagement with Facebook, attendance status, reasons for attending the festival and the combinations of forms of value that they perceived were identified. Research limitations/implications Future research should use a large-scale survey method to obtain a representative sample that is generalisable to a specific population of music festival-goers. Practical implications Dominance of features on Facebook providing festival-goers with functional value suggests they prefer a passive or co-optation approach to value co-creation in this context. Due to the limited extent of participants actively co-creating value on this platform, alternative means of encouraging interaction to co-create value with festival-goers should be investigated. Originality/value This study demonstrates that this SNS provides this group of young adults with a means to connect their real-time festival experience, with their on-line Facebook social network during the year.

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Approaches Based on Artificial Intelligence and the Internet of Intelligent Things to Prevent the Spread of COVID-19: Scoping Review (Preprint)

10.2196/preprints.19104 ◽

2020 ◽

Author(s):

Aya Sedky Adly ◽

Afnan Sedky Adly ◽

Mahmoud Sedky Adly

Keyword(s):

Artificial Intelligence ◽

Health Care ◽

Resource Allocation ◽

Modeling And Simulation ◽

Large Scale ◽

Information Gathering ◽

The Internet ◽

Experimental Therapies ◽

Computer Scientists ◽

And Control

BACKGROUND Artificial intelligence (AI) and the Internet of Intelligent Things (IIoT) are promising technologies to prevent the concerningly rapid spread of coronavirus disease (COVID-19) and to maximize safety during the pandemic. With the exponential increase in the number of COVID-19 patients, it is highly possible that physicians and health care workers will not be able to treat all cases. Thus, computer scientists can contribute to the fight against COVID-19 by introducing more intelligent solutions to achieve rapid control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the disease. OBJECTIVE The objectives of this review were to analyze the current literature, discuss the applicability of reported ideas for using AI to prevent and control COVID-19, and build a comprehensive view of how current systems may be useful in particular areas. This may be of great help to many health care administrators, computer scientists, and policy makers worldwide. METHODS We conducted an electronic search of articles in the MEDLINE, Google Scholar, Embase, and Web of Knowledge databases to formulate a comprehensive review that summarizes different categories of the most recently reported AI-based approaches to prevent and control the spread of COVID-19. RESULTS Our search identified the 10 most recent AI approaches that were suggested to provide the best solutions for maximizing safety and preventing the spread of COVID-19. These approaches included detection of suspected cases, large-scale screening, monitoring, interactions with experimental therapies, pneumonia screening, use of the IIoT for data and information gathering and integration, resource allocation, predictions, modeling and simulation, and robotics for medical quarantine. CONCLUSIONS We found few or almost no studies regarding the use of AI to examine COVID-19 interactions with experimental therapies, the use of AI for resource allocation to COVID-19 patients, or the use of AI and the IIoT for COVID-19 data and information gathering/integration. Moreover, the adoption of other approaches, including use of AI for COVID-19 prediction, use of AI for COVID-19 modeling and simulation, and use of AI robotics for medical quarantine, should be further emphasized by researchers because these important approaches lack sufficient numbers of studies. Therefore, we recommend that computer scientists focus on these approaches, which are still not being adequately addressed.

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Pattern of Coronary Artery Stenosis among Ischaemic Heart Disease Cases in Chittagong

Medicine Today ◽

10.3329/medtoday.v28i1.30969 ◽

2017 ◽

Vol 28 (1) ◽

pp. 30-31

Author(s):

Abu Tarek Iqbal ◽

Jalal Uddin ◽

Dhiman Banik ◽

Salehuddin ◽

Hasan Mamun ◽

...

Keyword(s):

Coronary Artery ◽

Sample Size ◽

Large Scale ◽

Resource Constraints ◽

Coronary Artery Stenosis ◽

Small Sample Size ◽

Sampling Technique ◽

Small Sample ◽

Artery Stenosis ◽

Study Results

Many studies were conducted on the topic over the whole world but there is none in Chittagong, Bangladesh. To know the pattern of coronary artery stenosis in Chittagong we have conducted the study because it is important for effective case management. It was an observational study. Convenient sampling technique was used and sample size was fixed to 110 considering resource constraints. All the cases were diagnosed on the basis of history, clinical features and laboratory investigations. Coronary artery angiogram was methodically conducted. All relevant data had been recorded and were managed manually. The findings were validated statistically. Discussion was made with updated literature review and finally conclusion was drawn. Total 110 cases were studied. Stenosis was found in 77(70%) cases. Among them 83% were male and 17% were female. Age range was 30-80 years but 76% cases were of 40-60 years age group. Among the stenosed cases SVD 29%, DVD 20% and TVD 20% only. Only 01% was LMCA. Commonest stenosed vessel was LAD 71%. RCA 60%, LCX 58% and LMCA 6%. 47% of stenosed cases were found with normal ECG. Ejection fraction of 57% stenosed cases was >55%. Study results are not significantly apart from studies in home and abroad. The limitation is small sample size. So, a multicenter study on a large scale cases is hereby advocated for a conclusive opinionMedicine Today 2016 Vol.28(1): 30-31

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