scholarly journals AI for Doctors—A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging

Healthcare ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1278
Author(s):  
Dennis M. Hedderich ◽  
Matthias Keicher ◽  
Benedikt Wiestler ◽  
Martin J. Gruber ◽  
Hendrik Burwinkel ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Drop Out ◽  
Medical Professionals ◽  
High Demand ◽  
Course Content ◽  
Drop Out Rate ◽  
Before And After ◽  
Successful Education ◽  
Substantial Drop

Successful adoption of artificial intelligence (AI) in medical imaging requires medical professionals to understand underlying principles and techniques. However, educational offerings tailored to the need of medical professionals are scarce. To fill this gap, we created the course “AI for Doctors: Medical Imaging”. An analysis of participants’ opinions on AI and self-perceived skills rated on a five-point Likert scale was conducted before and after the course. The participants’ attitude towards AI in medical imaging was very optimistic before and after the course. However, deeper knowledge of AI and the process for validating and deploying it resulted in significantly less overoptimism with respect to perceivable patient benefits through AI (p = 0.020). Self-assessed skill ratings significantly improved after the course, and the appreciation of the course content was very positive. However, we observed a substantial drop-out rate, mostly attributed to the lack of time of medical professionals. There is a high demand for educational offerings regarding AI in medical imaging among medical professionals, and better education may lead to a more realistic appreciation of clinical adoption. However, time constraints imposed by a busy clinical schedule need to be taken into account for successful education of medical professionals.

Role of Tablets as Mood Elevators in the Perception Towards Green Schools

2019 ◽  
pp. 69-97
Author(s):  
Rekha Verma ◽  
Atul Razdan
Keyword(s):  
School Curriculum ◽  
Learning By Doing ◽  
Drop Out ◽  
Educational Module ◽  
Green Schools ◽  
Course Content ◽  
Drop Out Rate ◽  
Green School ◽  
Depth Interviews

A green school basically integrates nature into school (mainly through academics, operations, and student/teacher and community engagement) with incorporated natural substance to school educational module. The sole purpose of green schools is to inculcate healthy and nature friendly initiatives with integrated environmental course content in school curriculum. Research shows that environmental training and education might enhance a normal learner's classroom execution and diversified impact on individual's personality as environmental knowledge can make ordinary learners extraordinary. Green schools aim at decreasing the drop-out rate in schools by introducing environmental education as an interesting subject with aspects of learning by doing. Students of Class 6th, 7th, and 8th standard use tabs/tablets for submitting their assignments, tests, and quiz/assessment exams enabling them to be tech-savvy generation. This research will address this issue through a qualitative research and in-depth interviews of students of different green schools of Gujarat.

Entwicklung und Evaluation einer internetbasierten begleiteten Selbsthilfe-Intervention zur Bewältigung von Albträumen

2015 ◽  
Vol 63 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Max Böckermann ◽  
Annika Gieselmann ◽  
Marjolijn Sorbi ◽  
Reinhard Pietrowsky
Keyword(s):  
Drop Out ◽  
Drop Out Rate

Hintergrund: Dieser Artikel beschreibt die Entwicklung eines internetbasierten begleiteten Selbsthilfetrainings (Albtraumcoach) zur Bewältigung von Albträumen, das innerhalb zweier Pilotstudien auf seine Durchführbarkeit und Anwendbarkeit getestet wurde. Methoden: Innerhalb eines neunstufigen Modells wird die Entwicklung der Intervention beschrieben. Dabei wird neben der wissenschaftlichen Evidenz, die die Basis für die Intervention bildet, auf technische, ethische, datenschutzrechtliche und weitere spezifische Maßnahmen innerhalb der Interventionsentwicklung eingegangen. In zwei Pilotstudien evaluierten zudem 10 Personen mit schlechten Träumen in der Vergangenheit die Durchführbarkeit (Studie 1) und 12 Personen mit wiederkehrenden Albträumen die Anwendbarkeit sowie den Nutzen der Intervention (Studie 2). Abhängige Variablen waren die Qualität der einzelnen Sitzungen, die Zufriedenheit mit der Intervention sowie Albtraumfrequenz, Albtraumbelastung, Schlafqualität und Depressivität. Ergebnisse und Diskussion: Die Durchführbarkeit und Anwendbarkeit des Trainings wurden positiv beurteilt. Während die Drop-out-Rate verhältnismäßig hoch war, ergaben sich erste, zurückhaltend zu beurteilende, Hinweise für einen Nutzen der Intervention.

Ohrakupunktur in der Therapie alkohol- und substanzbezogener Störungen – eine Übersicht

2004 ◽  
Vol 50 (3) ◽  
pp. 196-203 ◽  
Author(s):  
Stephanie Kunz ◽  
Michael Schulz ◽  
Gabriele Syrbe ◽  
Martin Driessen
Keyword(s):  
Drop Out ◽  
Randomisierte Kontrollierte Studien ◽  
Drop Out Rate ◽  
Kontrollierte Studien ◽  
Methodische Qualität

<B>Fragestellung:</B> Lässt die wissenschaftliche Datenlage positive Behandlungseffekte durch Ohrakupunktur in der Entzugsbehandlung von Alkohol- und Opiatabhängigen erwarten? </P><P> <B>Methodik:</B> Die im Rahmen der Recherche gefundenen Studien bezogen sich auf den Entzug von Alkohol (sechs) und von Kokain und Opiaten (acht). Die Studien wurden auf ihre methodische Qualität hin überprüft. </P><P> <B>Ergebnisse:</B> Es konnten 14 randomisierte kontrollierte Studien (RCT) zu Ohrakupunktur in der Behandlung von Alkohol- und Opiatabhängigkeit identifiziert werden. Dabei weisen die meisten Studien methodische Mängel auf. Ein Vergleich der Studien ist aufgrund unterschiedlicher Paradigmen kaum möglich, die Drop Out Rate liegt häufig über 20%. </P><P> <B>Schlussfolgerung:</B> Insgesamt reicht die verfügbare wissenschaftliche Datenlage nicht aus, um eine positive Wirkung der Akupunktur bei substanzbezogenen Störungen als gesichert anzunehmen.

Effectiveness of Classification Measures in Predicting Achievement in the Israel Defence Forces - Fitness Instruction Trainers Courses as a Case Study

2012 ◽  
Vol 21 (5-6) ◽  
pp. 145-172
Author(s):  
Yair Galily ◽  
Orly Kayam ◽  
Michael Bar-Eli
Keyword(s):  
Training System ◽  
Drop Out ◽  
Validity And Reliability ◽  
Screening Process ◽  
Training Course ◽  
Drop Out Rate ◽  
Army Service ◽  
Israeli Army ◽  
Israel Defense Forces

Abstract Human resources are the most crucial element in the selection of suitable fitness instruction trainers (FIT) and the results of the screening process impact greatly on the entire physical training system in the Israeli army, both in the short-term and the long-term (potential officers, young officers and developing and veteran officers). The aim of the current study is to examine the effectiveness, validity and reliability of the screening process for acceptance to the female fitness instructors training course in the Israel Defense Forces (IDF). The screening process aims to identify those that are most suitable from a large pool of candidates, in order to ensure the highest possible level of candidates and the lowest possible drop-out rate from the training course and subsequent army service. The paper examines the reliability of the classification exam currently administered in the course and its validity in predicting those candidates who will succeed in the course and in their assignments afterwards. The sample is based on a data analysis of nine screening dates over three years (three each year). The evaluation of validity is based on the relationship between the course entrance exam grades (administered a year before enlistment), exam grades at the beginning of the course and additional data relating to success in the field.

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

scholarly journals SARS-CoV-2 diagnosis using medical imaging techniques and artificial intelligence: A review

2021 ◽  
Vol 76 ◽  
pp. 6-14
Author(s):  
Narjes Benameur ◽  
Ramzi Mahmoudi ◽  
Soraya Zaid ◽  
Younes Arous ◽  
Badii Hmida ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Imaging Techniques

scholarly journals Potential Virus Involvement in Alzheimer’s Disease: Results from a Phase IIa Trial Evaluating Apovir, an Antiviral Drug Combination

2021 ◽  
pp. 1-19
Author(s):  
Nina Lindblom ◽  
Lars Lindquist ◽  
Jacob Westman ◽  
Mikael Åström ◽  
Roger Bullock ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Drug Combination ◽  
Antiviral Treatment ◽  
Antiviral Drug ◽  
Disease Process ◽  
Drop Out ◽  
Large Drop ◽  
Drop Out Rate

Background: Accumulating data suggest infectious agents are involved in Alzheimer’s disease (AD). The two primary aims of this trial were to assess safety and efficacy of an antiviral drug combination on AD progression. Objective: The trial evaluated whether Apovir, a combination of two antiviral agents, pleconaril (active on enteroviruses) and ribavirin (active on several viruses), could slow AD progression. Methods: Sixty-nine patients 60–85 years were treated with Apovir or placebo for 9 months and followed until 12 months after end of treatment. Cognitive tests, safety, biomarkers, drug plasma, and cerebrospinal fluid concentrations were assessed. Results: The tolerability of Apovir was compromised as demonstrated by the large drop-out rate and increased frequency and severity of adverse events. The primary endpoint, demonstrating a difference in change from baseline to 9 months between groups in ADAS-cog total score, was not met (p = 0.1809). However, there were observations indicating potential effects on both ADAS-cog and CDR-SB but these effects need to be verified. Also, there was a decrease in cerebrospinal fluid amyloid-β in Apovir at 9 months (p = 0.0330) but no change in placebo. Conclusion: This was the first randomized, placebo controlled clinical trial exploring antiviral treatment on AD progression. The trial is considered inconclusive due to the large drop-out rate. New trials are needed to verify if the indications of effect observed can be confirmed and which component(s) in Apovir contributed to such effects. Pleconaril alone may be studied to improve the tolerability and to verify if enterovirus is involved in the disease process.

scholarly journals Service Use, Drop-Out Rate and Clinical Outcomes: A Comparison Between High and Low Intensity Treatments in an IAPT Service

2014 ◽  
Vol 42 (6) ◽  
pp. 747-759 ◽  
Author(s):  
Stella W. Y. Chan ◽  
Malcolm Adams
Keyword(s):  
Clinical Outcomes ◽  
High Intensity ◽  
Recovery Rate ◽  
Service Use ◽  
Evaluation Study ◽  
Drop Out ◽  
Stepped Care ◽  
Depression And Anxiety ◽  
Low Intensity ◽  
Drop Out Rate

Background: The IAPT services provide high and low intensity psychological treatments for adults suffering from depression and anxiety disorders using a stepped care model. The latest national evaluation study reported an average recovery rate of 42%. However, this figure varied widely between services, with better outcomes associated with higher “step-up” rates between low and high intensity treatments. Aims: This study aimed to compare the two intensity groups in an IAPT service in Suffolk. Method: This study adopted a between groups design. A sample of 100 service users was randomly selected from the data collected from an IAPT service in Suffolk between May 2008 and February 2011. The treatment outcomes, drop-out rate, and other characteristics were compared between those who received high and low intensity treatments. Results: The high intensity group received, on average, more sessions and contact time. They received more CBT sessions and less guided self-help. There were no group differences in terms of the drop-out and appointment cancellation rates. Analyses on clinical outcomes suggested no group difference but demonstrated an overall recovery rate of 52.6% and significant reduction in both depression and anxiety symptoms. Conclusions: Despite methodological limitations, this study concludes that the service as a whole achieved above-average clinical outcomes. Further research building upon the current study in unpacking the relative strengths and weaknesses for the high and low intensity treatments would be beneficial for service delivery.

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