Intelligent Training Research Articles

421 Pathologist consensus for diagnostic labels is crucial in the developement of artificial intelligence training data in dermatology

421 Pathologist consensus for diagnostic labels is crucial in the developement of artificial intelligence training data in dermatology

Equipping AI for Unbiased and Inclusive Neurology

This Viewpoint advocates for inclusive artificial intelligence (AI) training and iterative testing and cautions against the uncritical adoption of AI engines that are trained on median patient groups and exclude the outlier groups that neurology regularly treats.

Emotional intelligence training among the healthcare workforce: a systematic review and meta-analysis.

The healthcare sector is acknowledged as a complex and challenging field. Increasingly, research highlights the importance of healthcare workers' internal social and emotional skills in managing their well-being and enhancing their capacity to provide patient care and support to colleagues. Emotional Intelligence (EI) has been identified as a key factor in improving the health and performance of healthcare workers, leading to the implementation of numerous programs aimed at enhancing EI. This meta-analysis aims to evaluate the effectiveness of EI training interventions among healthcare workers, focusing on various intervention designs and their impact on EI improvement. The review encompassed 17 longitudinal studies, each implementing EI training interventions for healthcare workers aged 18 and over. The studies employed a variety of research designs. All studies demonstrated an increase in EI following the intervention. However, methodological limitations within these studies might have led to an overestimation of the actual effects of the interventions. While the reviewed studies indicate a positive trend in EI enhancement post-intervention, the potential overestimation of effects due to methodological flaws necessitates caution. The findings underline the need for future research to explore the optimal duration and delivery methods for EI training in healthcare settings. The systematic review and meta-analysis have been pre-registered with PROSPERO [CRD42023393760]. Further details can be accessed at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023393760.

Psycho-social variable and cybercrime among library users in tertiary institutions in Cross River State Nigeria

Investigating cybercrime and the psycho-social variable among library users in tertiary institutions in Cross River State, Nigeria, was the aim of this study. Three objectives and research questions were developed to help the study accomplish its goal. The variables under investigation guided the completion of the literature review. For this study, a survey research design was chosen. For the study, a sample of five hundred and five (505) respondents was chosen. Purposive sampling was used in the selection process to guarantee that each faculty sample method was equally represented. This came to eight (8) tertiary institutions in all. 10% of the library's patrons were then chosen by accidently sampling them. A statistical analysis method called Pearson Product Moment Correlation Analysis was used to evaluate the research ideas. Because of the characteristics of the variables included in the investigation, this statistical method was employed. Every hypothesis was tested using relative degrees of freedom and at the .05 level of significance. The analysis's conclusions showed a relationship between cybercrimes in tertiary institutions and self-esteem, emotional intelligence, and gender. Based on the findings of the study it was recommended among others that management should adopt and Implement Psychological Support Services, integrated emotional intelligence training services, and promote gender-sensitive cyber security initiatives in the library.

Determination of artificial intelligence literacy and attitudes towards artificial intelligence of teachers working with gifted students and examining them according to some variables

This research aimed to determine the level of artificial intelligence literacy and attitudes towards artificial intelligence of teachers working with gifted students and to examine the results according to some variables. The study was conducted with the participation of 107 science and art center (BİLSEM) teachers selected by convenience sampling method. Data were collected using the Artificial Intelligence Literacy Scale and the General Attitude Towards Artificial Intelligence Scale. The findings show that teachers generally have high levels of artificial intelligence literacy and attitudes towards artificial intelligence. In gender comparisons, it was found that male teachers had higher AI literacy and attitudes than female teachers. Other variables such as age, professional experience, working time in BİLSEM, education level and branch did not have a significant effect on artificial intelligence literacy and attitude. As a result, it was observed that the knowledge and attitudes of teachers working with gifted students towards artificial intelligence were generally positive, but there were gender differences. Therefore, it is recommended that teachers' access to artificial intelligence training and professional development opportunities should be increased and especially female teachers' knowledge and attitudes towards technology should be improved.

Exploring the Interplay Between Self-Confidence and Emotional Intelligence in College-Level Educators: Implications for Teaching Effectiveness and Student Engagement

This study explores the relationship between self-confidence and emotional intelligence in college-level educators and examines their combined impact on teaching effectiveness and student engagement. As modern educational demands evolve, educators are increasingly recognized for their role in not only delivering content but also in fostering an inclusive, emotionally supportive learning environment. Self-confidence enables educators to present material with clarity, maintain authority, and adapt to diverse classroom challenges, while emotional intelligence equips them with empathy, self-awareness, and social skills essential for connecting with students on a personal level. The interplay of these traits contributes to a balanced teaching approach that supports both academic and emotional needs in students, thereby promoting active engagement, participation, and a positive classroom climate. This study utilizes a mixed-methods approach, combining quantitative self assessments and qualitative interviews to capture the nuanced ways in which self-confidence and emotional intelligence interact and influence teaching dynamics. Findings indicate that educators who possess both high self-confidence and emotional intelligence create classrooms that encourage open communication, foster psychological safety, and inspire student motivation. However, several limitations are noted, including the subjective nature of self-reported data and the influence of cultural and contextual factors on perceptions of confidence and emotional intelligence. Additionally, the study's cross-sectional design limits insights into the long-term development of these traits in educators. Despite these limitations, the study underscores the critical role of emotional and interpersonal skills in effective teaching, suggesting that professional development programs should integrate training in self-confidence and emotional intelligence to enhance educators’ overall impact. These findings contribute to a growing body of literature advocating for a holistic approach to educator preparation, one that values emotional acumen and self-assuredness alongside academic expertise. By emphasizing the importance of these traits, institutions can better support educators in creating enriching, engaging, and resilient learning environments that prepare students for both academic success and personal growth.

Improving Malaysian Undergraduates’ Emotional Intelligence Skills through Emotional Intelligence Training Program

Improving Malaysian Undergraduates’ Emotional Intelligence Skills through Emotional Intelligence Training Program

Evaluation of the effect of artificial intelligence training equipment in physical training of table tennis players from a biomechanical perspective

In table tennis competitions, the movement data of table tennis players plays an important role in daily training. In recent years, artificial intelligence technology has been widely used in sports competitions. With the development of artificial intelligence, how to use artificial intelligence to analyze sports video to obtain sports data of athletes has become more and more important. This paper is to use artificial intelligence to research and analyze the athletes in the table tennis competition, and then obtain the sports data of the athletes. This has important guiding significance for athletes and coaches in their daily training. Table tennis is a widely developed sport in China, and as China’s “national ball”, table tennis has always been in a leading position in the world table tennis competitions. It is widely loved by the public for its simple and easy access to sports facilities, low site requirements and sports methods. In this study, mathematical statistics and experimental methods were used. Combined with the application of the functional sports screen function test, 20 table tennis players from Shandong Sport University were selected as the test objects, and their sports performance was tested. The total score of 10 first-level athletes was 162 points, and the average score was 16.2 points. The total score of the 10 second-level athletes was 144 points, and the average score was 14.4 points. The performance of the first-level athletes was significantly higher than that of the second-level athletes. It showed that the first-level athletes were generally better than the second-level athletes in all aspects.

Multi-Institutional Evaluation and Training of Breast Density Classification AI Algorithm Using ACR Connect and AI-LAB

ObjectiveTo demonstrate and test the capabilities of the ACR Connect and AI-LAB software platform by implementing multi-institutional artificial intelligence (AI) training and validation for breast density classification. MethodsIn this proof-of-concept study, six US-based hospitals installed Connect and AI-LAB. A breast density algorithm was trained and tested on retrospective mammograms. We recorded time to receive institutional review board approval, to install software locally, and to complete the testing and training. We calculated the performance of the breast density algorithm at each participating hospital and compared it to the performance of a holdout multi-institutional clinical trial testing dataset and a retrospective multi-institutional dataset. We calculated the performance of the locally fine-tuned models on the holdout test datasets. ResultsThe median time to receive institutional review board approval was 66 days, and the median time to successfully install Connect and AI-LAB locally was 157 days. The median time to complete breast density algorithm testing and training was 216 days. The breast density algorithm performed worse at each hospital than on the holdout test dataset, suggesting poor generalizability of the base model. The fine-tuned models had mixed performance locally and performed poorly on the test dataset. DiscussionIn this study, we demonstrate the successful installation and implementation of Connect and AI-LAB software platforms at six facilities using a breast density algorithm. Our results suggest poor generalizability of an algorithm trained on a single dataset and algorithms fine-tuned at individual institutions, emphasizing the hypothetical importance of multi-institutional testing and training.

Language of emotions: Establishing connection with customers in tourism industries

Establishing a deep connection to customers is crucial in the highly competitive tourism industry. Service providers in the tourism industry must be good expressive communicators in order to deliver a better product and enhance the customer’s experience. This qualitative study explores the significance of the 'Language of Emotions' in the tourism industry, including the use of empathy, emotional intelligence, and effective communication to comprehend and address the emotional requirements of consumers. Tapping twelve (12) frontline tourism industry workers with at least three years of experience and twelve (12) tourists who made six purchases of tourism-related goods in the previous two years totaling to 24 respondents via purposive sampling, results of this study implies that tourism industry professionals can use this language to develop unique experiences, cultivate client loyalty, and accelerate company expansion. Personalized service delivery, emotional engagement, and attentive listening are some strategies. The study also highlights the necessity of providing personnel with communication and emotional intelligence training. The usefulness and difficulties of applying the "Language of Emotions" are covered in the conclusion, along with suggestions for further study and use. For tourism industry experts looking to improve client satisfaction and loyalty through emotional connections, this research provides insightful information.

Development and Validation of the Emergency Medical Technicians Occupational Stress Scale

Introduction. The population of interested workers for this study included Emergency Medical Technicians (EMTs) in the United States. This group of workers was chosen because of the nature of their work, which requires their presence at the scenes of life and death situations. Certainly, their work conditions can have an effect on their psychological well-being. Yet, the work of these workers, with all of its stressors, has not been adequately studied through the use of appropriate measuring instruments. Emergency Medical Technicians are not unknown in occupational stress research. This report discusses previous studies on EMT workers and occupational stressors and explains the curative process through the development and validation of an EMT Occupational Stress Scale. The report also highlights the psychometric investigation of this scale. Paramedics/EMTs face increased risk of physical and psychological stress due to the nature of their work. It is crucial to understand the stressors affecting their well-being in order to develop appropriate management strategies. Research suggests that EMTs may lack preparation for their roles, requiring additional training in empathy and emotional intelligence. The relationship between stressors experienced and clinical service provided needs further investigation. Standardized measures of stress for paramedics/EMTs are lacking and more comprehensive instruments are needed. This report aims to develop a comprehensive stress scale specifically for EMTs/paramedics, addressing validation concerns and incorporating environmental stress within a larger theoretical framework. Methods. This study was This study was conducted using a mixed-methods approach to develop and validate the Emergency Medical Technicians Occupational Stress Scale. The scale was pilot tested with a sample of EMTs to ensure reliability and validity. by the ethics committee and is based on a literature review. The Canadian EMT Job Satisfaction Questionnaire was used to measure organizational stress levels of EMTs. The questionnaire was reviewed by professionals and academics, resulting in the inclusion of five new items. The final item list consisted of 58 questions. Permission was obtained. Results. The outcomes and findings obtained from the comprehensive study conducted on the Development and Validation of the Emergency Medical Technicians Occupational Stress Scale have shed light on significant discoveries pertaining to the intricate realm of stress levels experienced by our dedicated EMT professionals. Conclusion. The rapidly evolving scope of Emergency Medical Services (EMS) practice has placed increasing demands on the relatively small professional community that consists of EMTs and paramedics. An Occupational Stress model was developed to examine interpersonal work stressors unique to the EMT role, and a measure was developed to assess the construct. Initial results suggest that the OSM is an accurate, reliable, and potentially valuable assessment tool. High levels of interpersonal stress may influence the EMTs to cope with their daily activities by seeking outlets for tension and depression through increased use of alcohol, legal drugs, and caffeine. Alcohol is used more frequently than other legal drugs are to modify interpersonal stress symptoms. The EMTs are in a prime position to help each other identify these symptoms when arising and offer assistance. Staff stress management programs are essential in solving and preventing occupational stress. A move toward prevention rather than reaction to such stress, which for many results in alcoholism, drug addiction, or job related emotional illness, will serve to preserve the health of the EMTs. The medical community has a vested interest in the health of these dedicated professionals. Not only does such prevention attempt to manage the human tragedy of alcoholism, legal drug addiction, and job related emotional illness, but it also prevents the more tangible, but no less important cost factors to the EMT.

Analysing the Factors Impacting the Mindfulness and Wellbeing of Faculty Members of Arts and Science Self-Financing Colleges in Kerala

Teaching in the modern academic environment is more complex, which makes it necessary to examine the challenges Kerala’s self-finance institutions arts and science institutes’ staff members are experiencing. This study investigates workplace stress among academic staff in self-financing arts and science institutes in Kerala. It analyses stress management techniques, including wellbeing initiatives and emotional intelligence training, and identifies the main stressors based on knowledge management (KM). The goal of the study is to improve faculty members’ performance and wellbeing in these institutions by providing information regarding relevant stress-reduction techniques that are specific to KM. The factors causing workplace stress have been measured as (a) demographic factors, (b) institutional factors and (c) psychological factors. Also, the stress management activities for the faculty members were considered a wellbeing programme, emotional intelligence, training and development. Initially, data collection was performed and 156 faculty members worked in arts and science self-financing colleges of the Kerala district. For a survey, in accordance with the proposed hypothesis, a systematic questionnaire has been created and sent to the faculty members who operate in Kerala. Moreover, statistical tests were performed on the gathered data using structural equation modelling (SEM) techniques. This investigation has revealed the characteristics that affect the faculty and staff working for an organisation in terms of workplace stress and excellent fit. The findings reveal that demographic demographics, institutional issues and stress management strategies influence faculty members in Kerala’s arts and self-finance colleges.

Building a culture of excellence by transforming toxic corporate environments

The article explores the profound impact of corporate culture on organizational performance and employee well-being. It delves into the detrimental effects of toxic corporate culture, characterized by poor leadership, ineffective communication, high-stress levels, and unethical behavior, which collectively undermine productivity and morale. The study also examines the significant economic impact of toxic corporate culture, including decreased productivity, high employee turnover, increased absenteeism, reputational damage, legal and ethical costs, and reduced innovation. The article proposes a comprehensive framework for cultural transformation, emphasizing the importance of leadership development, emotional intelligence training, open communication, recognition and rewards, work-life balance initiatives, diversity and inclusion programs, conflict resolution training, and continuous learning and development. By implementing these evidence-based strategies, organizations can transition from toxic environments to thriving, healthy workplaces that foster excellence and sustainable success. This approach not only enhances employee satisfaction and engagement but also drives innovation and economic growth within the organization.

Application of deep learning for automatic detection of table tennis balls from an intelligent serving machine

The Intelligent Table Tennis Serving Machine (TTSM) has revolutionized table tennis training by simulating the variability and precision of human opponents. However, current systems lack the capability to track and analyze ball landing points, limiting comprehensive performance evaluation. To address this, we propose a novel approach utilizing YOLOv8 as the benchmark model for detecting table tennis balls launched by a TTSM, tailored to meet the demands of intelligent training systems. Our key innovation involves integrating a Res2Net architecture enhanced with a Non-local Attention Module (NLAM) and a Dilated Atrous Spatial Pyramid Pooling (DASPP) unit into the neck network. This design improves the network’s ability to integrate multi-scale local features, thereby enhancing global information processing. The DASPP module, with adaptive dilation convolution, ensures thorough context comprehension. Additionally, we incorporate an Omni-dimensional Dynamic Convolution (ODConv) module in the detection head, employing parallel strategies to learn diverse and complementary attention cues, further enhancing detection accuracy and robustness. To validate our method, we conducted evaluations using the publicly available OpenTTGames dataset and a self-constructed dataset comprising over 10,000 table tennis ball images captured in various environments. Experimental results indicate that our method enhances mAP0.5, Precision, and Recall by 2.3%, 5.1%, and 0.9% on the OpenTTGames dataset, and by 3%, 2%, and 1.6% on the self-built dataset, respectively. Finally, we describe the optimization process of the intelligent TTSM system, which leverages keyframe analysis of ball landing points to provide feedback, thereby enabling continuous performance improvement in subsequent phases.

Оптимизация расчета оптической силы интраокулярной линзы с использованием возможностей искусственного интеллекта

Purpose. Development of a technology for optimal formula determination of the IOL required optical power, based on the artificial intelligence (AI) and the individual clinical characteristics of the patient’s eye. Material and methods. A retrospective analysis of 1337 uncomplicated phacoemulsification with implantation of a monofocal IOL RAO100C (Rayner) was performed. For artificial intelligence training and models testing, a database was created containing 1080 clinical cases (1080 eyes); the process of filling the database was fully automated. The accuracy criterion for IOL prediction was the range of spheroequivalent (SE) values in the postoperative period <|0.5|. Results. A retrospective analysis showed that in uncomplicated cataract surgery, the accuracy of the target refraction achievement is high and does not go beyond ±0.5 D. 16 artificial intelligence models were developed and tested, of which 4 were selected based on accuracy metrics – 1 model for each formula (Barrett, Haigis, Holladay 2, HofferQ). The best models turned out to be DecisionTreeClassifier. Validation of AI models was carried out by comparing the choice of IOL diopter between the AI and an expert. All models showed an advantage over the expert. A software interface for this service was developed and implemented. Conclusion. A selective database has been created for training and testing artificial intelligence models that determine IOL optical power. A system has been developed to help a doctor make a decision to determine the required IOL optical power based on artificial intelligence, depending on the individual clinical characteristics of the patient’s eye. The high efficiency of the developed technology has been proven on a test model (90–95%). The program interface was developed and implemented. Key words: IOL calculation, artificial intelligence

Analysis of virtual simulation training teaching problems of intellectual property law based on real working situations

This article aims to take AI intelligent training software and real business drills of intellectual property as the training mode to carry out intellectual property-related training in fields such as data intellectual property creation, application, management, transformation, and education, and truly achieve the educational goal of integrating science, education and industry. First, innovate the intellectual property training platform. Through AI question-and-answer led by digital human images, introduce front-line practical experts in the field of intellectual property into the virtual simulation training teaching process, build a training scene for the entire chain protection of intellectual property and real working situations, and improve the practical effect of training and cultivating intellectual property talents. Second, deepen the social service system of intellectual property. Project team members guide students and trainees to actively participate in patent navigation, patent group projects, pilot projects, intellectual property protection projects, etc., exercise and promote the continuous improvement of the social service capabilities of various intellectual property talents. At the end of the article, it is proposed that while intellectual property law teaching adapts to the development needs of the digital age, it should take the construction and teaching application of a virtual simulation experiment platform in real work situations as the core, respond to the practical needs of social practice work, and improve students' ability to adapt to society. The organic integration of AI technology, digital human technology and practical training teaching of intellectual property law has certain reference significance for the realization of the metaverse vision.

EDUCATIONAL MANAGEMENT ASPECTS OF THE SOMATIC INTELLIGENCE

Somatic intelligence is a type of human intelligence that includes self-regulation, emotional awareness, and listening to the body. Analyzing the scientific literature, it becomes clear that there are few theoretical works and empirical studies of somatic intelligence in Lithuania, but this does not mean the absence of discourse. Recently, the concept of somatic intelligence has been actively explored in the foreign scientific field using concepts such as somatic awareness, body awareness or interoceptive awareness; creating different models that enable detailing and structuring the concept of somatic intelligence; when constructing assessment systems (questionnaires). The concept of somatic intelligence, from a theoretical point of view, is a new and rarely studied phenomenon that requires in-depth research on a global and (especially) Lithuanian scale. Analyzing the research field of somatic intelligence, it was found that somatic intelligence is of interest to many researchers in various aspects related to the topic of kinesthetics: concept development and modelling, evaluation, education and management processes. The aim of the research – to reveal the features of kinestethic and sensory cognitive processes as the somatic intelligence parts in the educational management. The method of empirical research of the work is qualitative, which is based on phenomenological methodology. The qualitative research method (instrument) is a semi-structured individual interview. For the qualitative research, questions were prepared based on the model of somatic intelligence. The research results showed that, the somatic intelligence of primary school students in Klaipėda city formal education institutions is developed in a rather complex way. Methods and means of developing sensory intelligence include: creating a positive atmosphere, creating a sense of trust and security; the use of educational senses to create knowledge, cultural and environmental knowledge, training of critical thinking; involvement of students' and teacher's feelings, use of feelings for the development of critical thinking. Kinesthetic intelligence training methods include: training of fine and gross motor skills; methods and tools promoting discipline, methods and tools for overcoming stress and solving problems; physical involvement through role playing and other games. Research results related to other aspects of somatic intelligence (emotional and spiritual intelligence) will be presented in next article.

Relationship between Emotional Intelligence and Leadership Abilities of Head Teachers of Girls Secondary Schools in District Rahim Yar Khan

The present study aims to measure emotional intelligence level leadership abilities and find out the relationship between emotional intelligence and leadership abilities of head teachers of girls' secondary school at district Rahim Yar Khan. This descriptive correlational nature study used a survey research design. Headteachers of girls’ secondary schools in the district of Rahim Yar Khan constituted the population of the study. The 96 head teachers contributed to data collection. An online questionnaire was used as a research tool for data collection. The collected data was analyzed by SPSS-22 and presented in tables and figures. The study found a significant positive correlation between the emotional intelligence and leadership abilities of secondary school head teachers at district Rahim Yar Khan. The researchers recommended that the head teachers be given proper training in emotional intelligence in order to provide them with sufficient know-how about emotional intelligence and teach them how to use it for handling and motivating the employees under their auspices. The researchers also recommended that the study be replicated in other districts and at different levels of education to pave the way for generalizing the results of studies already conducted in this regard.

Perceptions for Utilization of Artificial Intelligence among Early Pediatric Rehabilitation Practitioners: A Survey in Pakistan

Integration of Artificial Intelligence in clinical medicine is rapidly expanding, driven by advancements in computing and extensive datasets. Artificial Intelligence is primarily utilized to design diagnostic tools for numerous medical conditions. Objective: To assess perceptions of using Artificial Intelligence among early pediatric rehabilitation practitioners in Pakistan. Methods: A cross-sectional online survey was conducted from November 2023 to April 2024, targeting young Masters students of Physical Therapy specializing in Pediatric Care and early pediatric therapists across Pakistan. Nonprobability convenience sampling was utilized. Participants were recruited through mailing lists and social media platforms. The anonymous survey collected demographic data and explored participants' knowledge, expected benefits, fears, and practices regarding Artificial Intelligence using a structured questionnaire. Descriptive statistics were employed for data analysis. Results: A total of 120 participants, with a mean age of 26 years and 70% female representation, completed the survey. Approximately 39.1% had received Artificial Intelligence training during their medical education, and 48.3% had utilized Artificial Intelligence tools during their learning. Key findings included 93.3% believing that Artificial Intelligence will enhance medical training and 60.8% agreeing that Artificial Intelligence will improve healthcare access. Despite positive attitudes towards AI, 54.1% had not utilized AI in their practice, indicating a need for further professional education. Conclusion: It was concluded that the study highlights a generally positive perception of Artificial Intelligence among novice pediatric rehabilitation practitioners in Pakistan but underscores the need for comprehensive AI education and training.

Empathy and emotional intelligence in physiotherapy: Enhancing patient care and outcomes

This paper explores the critical role of empathy and emotional intelligence in physiotherapy, focusing on their impact on patient care and treatment outcomes. The study identifies key empathy skills, including reflective listening, emotional labeling, perspective-taking, empathic acknowledgment, and compassionate curiosity, as essential for building strong therapeutic relationships and enhancing patient satisfaction and adherence. Data from surveyed physiotherapists reveal that approximately 85% observed improved patient engagement when these skills were applied, with 70% noting increased patient satisfaction and 60% reporting a positive effect on the therapeutic alliance. However, the study also highlights challenges such as compassion fatigue, which affects about 40% of physiotherapists and can diminish their capacity for empathy. Strategies like regular self-care and professional development were shown to improve management of these challenges by 50%, underscoring the need for continuous training in emotional intelligence. The paper concludes that integrating empathy and emotional intelligence into physiotherapy practice not only fosters a culture of patient-centered care but also significantly improves patient outcomes and satisfaction. It recommends incorporating comprehensive training on these skills into physiotherapy education and providing ongoing professional development opportunities to sustain high-quality, empathetic care.