scholarly journals Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 2–Comparison of the Performance of Artificial Intelligence and Traditional Pharmacoepidemiological Techniques

2021 ◽  
Vol 11 ◽  
Author(s):  
Maurizio Sessa ◽  
David Liang ◽  
Abdul Rauf Khan ◽  
Murat Kulahci ◽  
Morten Andersen
Keyword(s):  
Artificial Intelligence ◽  
Observational Studies ◽  
English Language ◽  
Drug Reactions ◽  
Drug Induced ◽  
Artificial Intelligence Techniques ◽  
Lengths Of Stay ◽  
Ovid Medline ◽  
Meta Analyses ◽  
Better Than

Aim: To summarize the evidence on the performance of artificial intelligence vs. traditional pharmacoepidemiological techniques.Methods: Ovid MEDLINE (01/1950 to 05/2019) was searched to identify observational studies, meta-analyses, and clinical trials using artificial intelligence techniques having a drug as the exposure or the outcome of the study. Only studies with an available full text in the English language were evaluated.Results: In all, 72 original articles and five reviews were identified via Ovid MEDLINE of which 19 (26.4%) compared the performance of artificial intelligence techniques with traditional pharmacoepidemiological methods. In total, 44 comparisons have been performed in articles that aimed at 1) predicting the needed dosage given the patient’s characteristics (31.8%), 2) predicting the clinical response following a pharmacological treatment (29.5%), 3) predicting the occurrence/severity of adverse drug reactions (20.5%), 4) predicting the propensity score (9.1%), 5) identifying subpopulation more at risk of drug inefficacy (4.5%), 6) predicting drug consumption (2.3%), and 7) predicting drug-induced lengths of stay in hospital (2.3%). In 22 out of 44 (50.0%) comparisons, artificial intelligence performed better than traditional pharmacoepidemiological techniques. Random forest (seven out of 11 comparisons; 63.6%) and artificial neural network (six out of 10 comparisons; 60.0%) were the techniques that in most of the comparisons outperformed traditional pharmacoepidemiological methods.Conclusion: Only a small fraction of articles compared the performance of artificial intelligence techniques with traditional pharmacoepidemiological methods and not all artificial intelligence techniques have been compared in a Pharmacoepidemiological setting. However, in 50% of comparisons, artificial intelligence performed better than pharmacoepidemiological techniques.

scholarly journals Artificial Intelligence in Health in 2018: New Opportunities, Challenges, and Practical Implications

2019 ◽  
Vol 28 (01) ◽  
pp. 052-054
Author(s):  
Gretchen Jackson ◽  
Jianying Hu ◽  
Keyword(s):  
Artificial Intelligence ◽  
Domain Knowledge ◽  
English Language ◽  
Machine Learning Algorithms ◽  
Original Research ◽  
Domain Experts ◽  
Ovid Medline ◽  
Significant Research ◽  
Health Applications

Objective: To summarize significant research contributions to the field of artificial intelligence (AI) in health in 2018. Methods: Ovid MEDLINE® and Web of Science® databases were searched to identify original research articles that were published in the English language during 2018 and presented advances in the science of AI applied in health. Queries employed Medical Subject Heading (MeSH®) terms and keywords representing AI methodologies and limited results to health applications. Section editors selected 15 best paper candidates that underwent peer review by internationally renowned domain experts. Final best papers were selected by the editorial board of the 2018 International Medical Informatics Association (IMIA) Yearbook. Results: Database searches returned 1,480 unique publications. Best papers employed innovative AI techniques that incorporated domain knowledge or explored approaches to support distributed or federated learning. All top-ranked papers incorporated novel approaches to advance the science of AI in health and included rigorous evaluations of their methodologies. Conclusions: Performance of state-of-the-art AI machine learning algorithms can be enhanced by approaches that employ a multidisciplinary biomedical informatics pipeline to incorporate domain knowledge and can overcome challenges such as sparse, missing, or inconsistent data. Innovative training heuristics and encryption techniques may support distributed learning with preservation of privacy.

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.

High-Osmolar and Low-Osmolar Contrast Media

1993 ◽  
Vol 34 (3) ◽  
pp. 205-209 ◽  
Author(s):  
H. S. Thomsen ◽  
S. Dorph
Keyword(s):  
Contrast Media ◽  
Observational Studies ◽  
Randomized Trials ◽  
Iodinated Contrast Media ◽  
Intravascular Injection ◽  
Small Minority ◽  
The Past ◽  
Iodinated Contrast ◽  
Meta Analyses ◽  
Better Than

During the past 3 years a great number of papers about adverse drug reactions to intravascular injection of high-osmolar and low-osmolar iodinated contrast media (CM) have been published. They include observational studies, randomized trials, meta-analyses and committee reports. Thorough analysis of this material substantiates an improvement in safety of at least 6-fold using nonionic low-osmolar CM compared with ionic high-osmolar CM. The point where only a small minority is continuing to argue effectively that low-osmolar CM are not better than conventional high-osmolar CM has now been reached. High-osmolar CM are used less and less for intravascular purposes, and, in fact, have been totally replaced by low-osmolar CM in 4 countries.

scholarly journals Intraarticular Hyaluronic Acid Preparations for Knee Osteoarthritis: Are Some Better Than Others?

Cartilage ◽  
2021 ◽  
pp. 194760352110173
Author(s):  
David Webner ◽  
Yili Huang ◽  
Charles D. Hummer
Keyword(s):  
Hyaluronic Acid ◽  
Knee Osteoarthritis ◽  
Observational Studies ◽  
Sodium Hyaluronate ◽  
The United States ◽  
Osteoarthritis Of The Knee ◽  
Inclusion Criteria ◽  
Safety And Efficacy ◽  
Ovid Medline ◽  
Better Than

Objective This literature review summarizes evidence on the safety and efficacy of intraarticular hyaluronic acid (IAHA) preparations approved in the United States for the treatment of osteoarthritis of the knee. Design A systematic literature search was performed in PubMed, Ovid MEDLINE, and SCOPUS databases. Only studies in which clinical outcomes of individual IAHA preparations alone could be assessed when compared to placebo, no treatment, other standard knee osteoarthritis treatments, and IAHA head-to-head studies were selected. Results One hundred nine articles meeting our inclusion criteria were identified, including 59 randomized and 50 observational studies. Hylan G-F 20 has been the most extensively studied preparation, with consistent results confirming efficacy in placebo-controlled studies. Efficacy is also consistently reported for Supartz, Monovisc, and Euflexxa, but not for Hyalgan, Orthovisc, and Durolane. In the head-to-head trials, high-molecular-weight (MW) Hylan G-F 20 was consistently superior to low MW sodium hyaluronate preparations (Hyalgan, Supartz) up to 20 weeks, whereas one study reported that Durolane was noninferior to Supartz. Head-to-head trials comparing high versus medium MW preparations all used Hylan G-F 20 as the high MW preparation. Of the IAHA preparations with strong evidence of efficacy in placebo-controlled studies, Euflexxa was found to be noninferior to Hylan G-F 20. There are no direct comparisons to Monovisc. One additional IAHA preparation (ie, Synovial), which has not been assessed in placebo-controlled studies, was also noninferior to Hylan G-F 20. Conclusion IAHA efficacy varies widely across preparations. High-quality studies are required to assess and compare the safety and efficacy of IAHA preparations.

scholarly journals Incidence of Skin Cancer in Patients With Chronic Inflammatory Cutaneous Diseases on Targeted Therapies: A Systematic Review and Meta-Analysis of Observational Studies

2021 ◽  
Vol 11 ◽  
Author(s):  
Salvatore Crisafulli ◽  
Lucrezia Bertino ◽  
Andrea Fontana ◽  
Fabrizio Calapai ◽  
Ylenia Ingrasciotta ◽  
...  
Keyword(s):  
Observational Studies ◽  
Inflammatory Diseases ◽  
Meta Analysis ◽  
Drug Induced ◽  
Skin Cancers ◽  
Organ Systems ◽  
Risk Of Malignancy ◽  
Inflammatory State ◽  
Meta Analyses ◽  
Melanoma Skin

Cancer is one of the several comorbidities that have been linked with chronic cutaneous inflammatory diseases namely psoriasis/psoriatic arthritis and hidradenitis suppurativa. Although the chronic inflammatory state, typical of the diseases, may induce pro-tumorigenic effects, the debate whether or not the drugs currently used in clinical practice do in facts increase a patient’s risk of malignancy remains largely unsolved. The therapeutic armamentarium has been greatly enhanced at least in the last two decades with the advent of biologics, a heterogeneous group of laboratory-engineered agents with more in the pipeline, and other targeted small molecules. Among the organ systems, skin results as one of the most commonly affected, non-melanoma skin cancers being the main drug-induced manifestations as side effect in course of these treatments. The objective of the study is to systematically review the cutaneous malignancy risk of the newer therapies through an overview of meta-analyses and observational studies on the topic.

scholarly journals Contemporary Issues in Well-being of Undergraduate Clinical Students: A Systematic Review

2021 ◽  
Vol 13 (1) ◽  
pp. 3-16
Author(s):  
Chong Tze Lin ◽  
Lau Wee Ming ◽  
Tha Kyi Kyi
Keyword(s):  
Clinical Training ◽  
English Language ◽  
Well Being ◽  
Contributing Factors ◽  
Complex Concept ◽  
Ovid Medline ◽  
Emotional Aspect ◽  
Lack Of Exercise ◽  
Meta Analyses ◽  
Year 2000

Well-being is a complex concept with objective and subjective elements that contribute to life satisfaction. Medical students experience inevitable transition from pre-clinical to clinical training with increasingly more independence and responsibility. This study aimed to identify well-being issues in undergraduate clinical students. The emotional, physical, social, spiritual, occupational and intellectual aspects of well-being were focused on. A thorough literature search was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies reporting issues from the six aspects of well-being in undergraduate clinical students, and published in peer-reviewed journals in English language from the year 2000 to 2020 with full-text available online were included. The initial search from PubMed, OVID Medline, Psych INFO and CINAHL Plus retrieved 623 articles with 51 studies included in this review. Evidence from the previous studies demonstrated poor well-being among undergraduate clinical students. Stress, lack of exercise, low peer and family support, and mistreatment by clinicians and patients were common well-being issues encountered. Based on this literature review, the five aspects of well-being except the emotional aspect were less explored. Thus, it will be of interest to investigate well-being issues among Malaysian undergraduate clinical students from the physical and occupational aspects, which are further impacted by the COVID-19 pandemic, and to identify possible contributing factors. Undergraduate clinical students are faced with several well-being issues. Thus, early detection of these issues is important to avoid devastating consequences to students and patients.

A Survey on Artificial Intelligence Techniques to Prevent Cyber Crime

2018 ◽  
Vol 8 (5) ◽  
pp. 80
Author(s):  
Juveriya Afreen
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Data Security ◽  
Human Reasoning ◽  
Cyber Crime ◽  
Artificial Intelligence Techniques

Abstract-- With increase in complexity of data, security, it is difficult for the individuals to prevent the offence. Thus, by using any automation or software it’s not possible by only using huge fixed algorithms to overcome this. Thus, we need to look for something which is robust and feasible enough. Hence AI plays an epitome role to defense such violations. In this paper we basically look how human reasoning along with AI can be applied to uplift cyber security.

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