scholarly journals Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry—A Systematic Review

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Naseer Ahmed ◽  
Maria Shakoor Abbasi ◽  
Filza Zuberi ◽  
Warisha Qamar ◽  
Mohamad Syahrizal Bin Halim ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Full Text ◽  
Patient Management ◽  
English Language ◽  
Clinical Performance ◽  
Research Question ◽  
Time Saving ◽  
Artificial Intelligence Techniques ◽  
Clinical Scenarios

Objective. The objective of this systematic review was to investigate the quality and outcome of studies into artificial intelligence techniques, analysis, and effect in dentistry. Materials and Methods. Using the MeSH keywords: artificial intelligence (AI), dentistry, AI in dentistry, neural networks and dentistry, machine learning, AI dental imaging, and AI treatment recommendations and dentistry. Two investigators performed an electronic search in 5 databases: PubMed/MEDLINE (National Library of Medicine), Scopus (Elsevier), ScienceDirect databases (Elsevier), Web of Science (Clarivate Analytics), and the Cochrane Collaboration (Wiley). The English language articles reporting on AI in different dental specialties were screened for eligibility. Thirty-two full-text articles were selected and systematically analyzed according to a predefined inclusion criterion. These articles were analyzed as per a specific research question, and the relevant data based on article general characteristics, study and control groups, assessment methods, outcomes, and quality assessment were extracted. Results. The initial search identified 175 articles related to AI in dentistry based on the title and abstracts. The full text of 38 articles was assessed for eligibility to exclude studies not fulfilling the inclusion criteria. Six articles not related to AI in dentistry were excluded. Thirty-two articles were included in the systematic review. It was revealed that AI provides accurate patient management, dental diagnosis, prediction, and decision making. Artificial intelligence appeared as a reliable modality to enhance future implications in the various fields of dentistry, i.e., diagnostic dentistry, patient management, head and neck cancer, restorative dentistry, prosthetic dental sciences, orthodontics, radiology, and periodontics. Conclusion. The included studies describe that AI is a reliable tool to make dental care smooth, better, time-saving, and economical for practitioners. AI benefits them in fulfilling patient demand and expectations. The dentists can use AI to ensure quality treatment, better oral health care outcome, and achieve precision. AI can help to predict failures in clinical scenarios and depict reliable solutions. However, AI is increasing the scope of state-of-the-art models in dentistry but is still under development. Further studies are required to assess the clinical performance of AI techniques in dentistry.

Care of the Postpartum Patient in the Emergency Department: A Systematic Review with Implications for Maternal Mortality

2021 ◽  
Author(s):  
Kellie A. Mitchell ◽  
Alison J. Haddock ◽  
Hamad Husainy ◽  
Lauren A. Walter ◽  
Indranee Rajapreyar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Emergency Department ◽  
Maternal Mortality ◽  
Social Services ◽  
Full Text ◽  
Postpartum Period ◽  
English Language ◽  
Case Reports ◽  
Private Insurance ◽  
Maternal Deaths

Objective Approximately one-third of maternal deaths occur postpartum. Little is known about the intersection between the postpartum period, emergency department (ED) use, and opportunities to reduce maternal mortality. The primary objectives of this systematic review are to explore the incidence of postpartum ED use, identify postpartum disease states that are evaluated in the ED, and summarize postpartum ED use by race/ethnicity and payor source. Study Design We searched PubMed, Embase, Cumulative Index of Nursing and Allied Health Literature (CINAHL), ClinicalTrials.gov, Cochrane CENTRAL, Social Services Abstracts, and Scopus from inception to September 19, 2019. Each identified abstract was screened by two authors; the full-text manuscripts of all studies deemed to be potential candidates were then reviewed by the same two authors and included if they were full-text, peer-reviewed articles in the English language with primary patient data reporting care of a female in the ED in the postpartum period, defined as up to 1 year after the end of pregnancy. Results A total of 620 were screened, 354 records were excluded and 266 full-text articles were reviewed. Of the 266 full-text articles, 178 were included in the systematic review; of these, 108 were case reports. Incidence of ED use by postpartum females varied from 4.8 to 12.2% in the general population. Infection was the most common reason for postpartum ED evaluation. Young females of minority race and those with public insurance were more likely than whites and those with private insurance to use the ED. Conclusion As many as 12% of postpartum women seek care in the ED. Young minority women of lower socioeconomic status are more likely to use the ED. Since approximately one-third of maternal deaths occur in the postpartum period, successful efforts to reduce maternal mortality must include ED stakeholders. Systematic Review Registration CRD42020151126. Key Points

Recommender Systems in Digital Libraries Using Artificial Intelligence and Machine Learning

2021 ◽  
pp. 162-178
Author(s):  
Namik Delilovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Digital Libraries ◽  
Full Text ◽  
Text Search ◽  
Full Text Search ◽  
Artificial Intelligence Techniques ◽  
Search Results ◽  
Advanced Search ◽  
Search Field

Searching for contents in present digital libraries is still very primitive; most websites provide a search field where users can enter information such as book title, author name, or terms they expect to be found in the book. Some platforms provide advanced search options, which allow the users to narrow the search results by specific parameters such as year, author name, publisher, and similar. Currently, when users find a book which might be of interest to them, this search process ends; only a full-text search or references at the end of the book may provide some additional pointers. In this chapter, the author is going to give an example of how a user could permanently get recommendations for additional contents even while reading the article, using present machine learning and artificial intelligence techniques.

scholarly journals Built to last? The sustainability of health system improvements, interventions and change strategies: a study protocol for a systematic review

BMJ Open ◽  
2017 ◽  
Vol 7 (11) ◽  
pp. e018568 ◽  
Author(s):  
Jeffrey Braithwaite ◽  
Luke Testa ◽  
Gina Lamprell ◽  
Jessica Herkes ◽  
Kristiana Ludlow ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health System ◽  
Health Systems ◽  
Full Text ◽  
English Language ◽  
Secondary Data ◽  
Primary Data ◽  
Change Strategies ◽  
Screening Process ◽  
Sustainable Health

IntroductionThe sustainability of healthcare interventions and change programmes is of increasing importance to researchers and healthcare stakeholders interested in creating sustainable health systems to cope with mounting stressors. The aim of this protocol is to extend earlier work and describe a systematic review to identify, synthesise and draw meaning from studies published within the last 5 years that measure the sustainability of interventions, improvement efforts and change strategies in the health system.Methods and analysisThe protocol outlines a method by which to execute a rigorous systematic review. The design includes applying primary and secondary data collection techniques, consisting of a comprehensive database search complemented by contact with experts, and searching secondary databases and reference lists, using snowballing techniques. The review and analysis process will occur via an abstract review followed by a full-text screening process. The inclusion criteria include English-language, peer-reviewed, primary, empirical research articles published after 2011 in scholarly journals, for which the full text is available. No restrictions on location will be applied. The review that results from this protocol will synthesise and compare characteristics of the included studies. Ultimately, it is intended that this will help make it easier to identify and design sustainable interventions, improvement efforts and change strategies.Ethics and disseminationAs no primary data were collected, ethical approval was not required. Results will be disseminated in conference presentations, peer-reviewed publications and among policymaker bodies interested in creating sustainable health systems.

scholarly journals Everywhere is Nowhere: A Systematic Review of Menstrual Health and Hygiene Management (MHHM) as a Human Right

2020 ◽  
Author(s):  
Suruchi Sood ◽  
Sarah Stevens ◽  
Maho Okumura ◽  
Astha Ramaiya ◽  
Michael Hauer
Keyword(s):  
Systematic Review ◽  
Human Rights ◽  
Full Text ◽  
Child Protection ◽  
English Language ◽  
Grey Literature ◽  
Hygiene Management ◽  
Sanitation And Hygiene ◽  
Menstrual Health ◽  
Rights Issue

Abstract Background: In many countries, stigma surrounds menstruation, which impacts several Sustainable Development Goals, including good health, quality education, gender equality, and water and sanitation. Despite its relationship with several development issues, menstrual health and hygiene management among adolescents has until recently been ignored by practitioners and researchers. This paper is a systematic review of existing literature and argues that menstrual health and hygiene management is a human rights issue, cross-cutting through development domains of health, education, nutrition, child protection, and water, sanitation, and hygiene. Methods: Four coders independently screened PubMed, Academic OneFile, and Google Scholar to obtain articles using iterations of the key terms: menstrual health; adolescents; health outcomes; education; nutrition; water, sanitation, and hygiene; and child protection. English language primary studies in peer-reviewed or grey literature articles published after 2000, that mentioned adolescents, health or hygiene, and menstruation or menstrual were included. A 9-item scale was used to rate selected full-text articles as strong, moderate, or weak. Synthesis of the results were narrative and examined the relationships between menstrual health and hygiene management and the cross-cutting domains.Results: In total, 28,745 articles were screened, with 84 articles included in the full-text review and quality assessment. Nine articles were coded as “strong” (10.8%), 46 (55.4%) as “moderate,” and 28 (33.7%) as “weak.” More than 60% of the articles examined the relationship between menstrual health and hygiene management and health (37.3%) or water, sanitation, and hygiene (25.3%). Only 11 manuscripts examined menstrual health and hygiene management as a cross-cutting issue impacting more than one development domain.Conclusions: Access to adequate facilities and menstrual health and hygiene management resources are the most common relationships documented within literature. However, there is little focus on menstrual health and hygiene management in the context of other development domains, highlighting the fact that poor menstrual health and hygiene management has not been studied as a human rights issue, negatively impacting millions of girls. Using a cross-cutting, human rights framework to address inadequate menstrual health and hygiene management is fundamental to promoting menstrual health and hygiene management with dignity among girls and women across the globe.

scholarly journals Factors Affecting Panic Buying during COVID-19 Outbreak and Strategies: A Scoping Review

2021 ◽  
Author(s):  
Mohadeseh Motamed-Jahromi ◽  
Zahra Meshkani ◽  
Seyed Masood Mosavi-Negad ◽  
Victoria Momenabadi ◽  
Mahdieh Sadat Ahmadzadeh
Keyword(s):  
Scoping Review ◽  
Full Text ◽  
English Language ◽  
Data Extraction ◽  
Research Question ◽  
Self Assessment ◽  
Holistic View ◽  
Factors Affecting ◽  
Economic Strategies ◽  
Flow Of Information

Background: This study aimed to assess factors affecting panic buying and strategies to deal with them during COVID-19 with a scoping review. Method: The review was performed based on Arksey and O’Malley. PubMed, Embase, Scopus, ProQuest, and Science Direct databases were selected to search. All English language full-text articles from Jan 2020 to May 2021 were included. Initially, the titles and abstracts of the retrieved articles were read and screening was accomplished based on the research question. After that, the full text of eligible studies was examined. A third reviewer was resolved disagreements at any stage by a consensus meeting. A self-assessment form was designed for data extraction. The causes of panic buying were assessed as a descriptive study. Results: The search process returned 23 articles after deletion for complete data extraction and analysis. Through thematic analysis, the factors influencing panic buying were divided into six categories including cognitive, emotional, behavioral, social, and economic factors as well as government action, and finally, the recommended strategies were categorized in two categories included psychosocial and economic. Conclusion: A holistic view of panic buying’s causes allows planners and decision-makers to design categorized strategies beyond the suggested strategies. Increasing customer awareness and monitoring the flow of information through social media and mass media, psychotherapy, counseling, and economic strategies are considered by planners to combat panic buying.  

scholarly journals Estimating the incubation period of acute Q fever, a systematic review

2018 ◽  
Vol 146 (6) ◽  
pp. 665-672 ◽  
Author(s):  
D. Todkill ◽  
T. Fowler ◽  
J.I. Hawker
Keyword(s):  
Systematic Review ◽  
Incubation Period ◽  
Full Text ◽  
English Language ◽  
Q Fever ◽  
Expert Advice ◽  
Evidence Based ◽  
Individual Level ◽  
Level Data ◽  
Acute Q Fever

AbstractEstimates of the incubation period for Q fever vary substantially between different reviews and expert advice documents. We systematically reviewed and quality appraised the literature to provide an evidence-based estimate of the incubation period of the Q fever by the aerosolised infection route. Medline (OVIDSP) and EMBASE were searched with the search limited to human studies and English language. Eligible studies included persons with symptomatic, acute Q fever, and defined exposure toCoxiella burnetti. After review of 7115 titles and abstracts, 320 records were screened at full-text level. Of these, 23 studies contained potentially useful data and were quality assessed, with eight studies (with 403 individual cases where the derivation of incubation period was possible) being of sufficient quality and providing individual-level data to produce a pooled summary. We found a median incubation period of 18 days, with 95% of cases expected to occur between 7 and 32 days after exposure.

scholarly journals Artificial intelligence in gastrointestinal endoscopy for inflammatory bowel disease: a systematic review and new horizons

2021 ◽  
Vol 14 ◽  
pp. 175628482110177
Author(s):  
Gian Eugenio Tontini ◽  
Alessandro Rimondi ◽  
Marta Vernero ◽  
Helmut Neumann ◽  
Maurizio Vecchi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
Gastrointestinal Endoscopy ◽  
Early Stage ◽  
Real Life ◽  
Added Value ◽  
Clinical Scenarios ◽  
Inflammatory Bowel

Introduction: Since the advent of artificial intelligence (AI) in clinical studies, luminal gastrointestinal endoscopy has made great progress, especially in the detection and characterization of neoplastic and preneoplastic lesions. Several studies have recently shown the potential of AI-driven endoscopy for the investigation of inflammatory bowel disease (IBD). This systematic review provides an overview of the current position and future potential of AI in IBD endoscopy. Methods: A systematic search was carried out in PubMed and Scopus up to 2 December 2020 using the following search terms: artificial intelligence, machine learning, computer-aided, inflammatory bowel disease, ulcerative colitis (UC), Crohn’s disease (CD). All studies on human digestive endoscopy were included. A qualitative analysis and a narrative description were performed for each selected record according to the Joanna Briggs Institute methodologies and the PRISMA statement. Results: Of 398 identified records, 18 were ultimately included. Two-thirds of these (12/18) were published in 2020 and most were cross-sectional studies (15/18). No relevant bias at the study level was reported, although the risk of publication bias across studies cannot be ruled out at this early stage. Eleven records dealt with UC, five with CD and two with both. Most of the AI systems involved convolutional neural network, random forest and deep neural network architecture. Most studies focused on capsule endoscopy readings in CD ( n = 5) and on the AI-assisted assessment of mucosal activity in UC ( n = 10) for automated endoscopic scoring or real-time prediction of histological disease. Discussion: AI-assisted endoscopy in IBD is a rapidly evolving research field with promising technical results and additional benefits when tested in an experimental clinical scenario. External validation studies being conducted in large and prospective cohorts in real-life clinical scenarios will help confirm the added value of AI in assessing UC mucosal activity and in CD capsule reading. Plain language summary Artificial intelligence for inflammatory bowel disease endoscopy Artificial intelligence (AI) is a promising technology in many areas of medicine. In recent years, AI-assisted endoscopy has been introduced into several research fields, including inflammatory bowel disease (IBD) endoscopy, with promising applications that have the potential to revolutionize clinical practice and gastrointestinal endoscopy. We have performed the first systematic review of AI and its application in the field of IBD and endoscopy. A formal process of paper selection and analysis resulted in the assessment of 18 records. Most of these (12/18) were published in 2020 and were cross-sectional studies (15/18). No relevant biases were reported. All studies showed positive results concerning the novel technology evaluated, so the risk of publication bias cannot be ruled out at this early stage. Eleven records dealt with UC, five with CD and two with both. Most studies focused on capsule endoscopy reading in CD patients ( n = 5) and on AI-assisted assessment of mucosal activity in UC patients ( n = 10) for automated endoscopic scoring and real-time prediction of histological disease. We found that AI-assisted endoscopy in IBD is a rapidly growing research field. All studies indicated promising technical results. When tested in an experimental clinical scenario, AI-assisted endoscopy showed it could potentially improve the management of patients with IBD. Confirmatory evidence from real-life clinical scenarios should be obtained to verify the added value of AI-assisted IBD endoscopy in assessing UC mucosal activity and in CD capsule reading.

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