Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice

This comparative review explores the dynamic and evolving landscape of artificial intelligence(AI)-powered innovations within high-tech research and development(R&D).It delves into both theoreticalmodels and practical applications across a broad range of industries,including biotechnology,automotive,aerospace,and telecom-munications.By examining critical advancements in AI algorithms,machine learning,deep learning models,simulations,and predictive analytics,the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies.The review integrates both qualitative and quantitative data derived from academic studies,industry reports,and real-world case studies to showcase the tangible impacts of AI on product innovation,process optimization,and strategic decision-making.Notably,it discusses the challenges of integrating AI within complex industrial systems,such as ethical concerns,technical limitations,and the need for regulatory oversight.The findings reveal a mixed landscape where AI has significantly accelerated R&D processes,reduced costs,and enabled more precise simulations and predictions,but also highlighted gaps in knowledge transfer,skills adaptation,and cross-industry standardization.By bridging the gap between AI theory and practice,the review offers insights into the effectiveness,successes,and obstacles faced by organizations as they implement AI-driven solutions.Concluding with a forward-looking perspective,the review identifies emerging trends,future challenges,and promising opportunities inAI-poweredR&D,such as the rise of autonomous systems,AI-driven drug discovery,and sustainable energy solutions.It offers a holistic understanding of how AI is shaping the future of technological innovation and provides actionable insights for researchers,engineers,and policymakers involved in high-tech Research and Development(R&D).

Cultivation Path of Nursing Undergraduates’Scientific Research and Innovation Ability

Objective: The cultivation of the innovation ability and scientific research is one of the nursing learning objectives for undergraduate students. To explore the method and effect of training system of scientific research innovation ability of nursing undergraduates based on “3332”. Methods: Three course learning modules are constructed: stage-based course learning module, systematic project practice training module and comprehensive practice training module. A practical training platform for scientific research innovation projects is built, and undergraduate scientific research innovation ability training is carried out from both in-class and out-of-class lines. Results: Since 2017, the students have obtained 7 national innovation and entrepreneurship training programs, 52 university-level undergraduate scientific research projects, published more than 10 academic papers, and obtained 2 patent authorization. Conclusions: The training system of scientific research innovation ability of nursing undergraduates based on “3332” is conducive to the development of scientific research innovation ability of nursing students, and to cultivate nursing talents who can adapt to the development of the new era and have better post competence.

Producing Podcasts in a Chinese Classroom: A Digital Humanities Project

This action research which situates itself in the context of Digital Humanities focuses on engaging students of Introductory Chinese course with an assignment to create podcasts in the form of an interview.Requiring students to integrate the aural,oral,and textural information via technology so as to carry a conversation with an interlocutor challenges them to convey their thoughts from the language they think in into meaningful ideas using the target language.In this way,students are“pushed”to convert their listening,speaking,and writing from being isolated components into a more dynamic and cohesive mode of communicating.As they explore expressing their ideas in the language they are learning,they develop the skills and sensibility needed to critically analyze their own work.Although limited in scale,the podcast format urges students to transform what they need to learn into a familiar product.

Advances in machine learning-and artificial intelligence-assisted material design of steels

With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science.Machine learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data points.Compared with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials.This review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model evaluation.Then,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and performance.The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed.Finally,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed.

College English Teaching Study Conducted by Discovery Learning Theory and Action Research——Take College English Ⅱ for Instance

The unceasing revolution of the global economy and culture boosts the revolutionary step of the educational circle.Combining the creed of The Guide of College English Teaching in 2016 with the results of investigation and survey in colleges, a research group in the Institute of Foreign Languages of Hankou University comes up with a revolutionary trial scheme on College English teaching conducted by discovery learning theory, as well as a research method of action research, which is in hope of mending the problems and shortcomings of current College English teaching.

Recent progress in research and design concepts for the characterization,testing,and photocatalysts for nitrogen reduction reaction

The reduction of molecular nitrogen(N_(2))to ammonia(NH_(3))under mild conditions is one of the most promising studies in the energy field due to the important role of NH_(3)in modern industry,production,and life.The photocatalytic reduction of N_(2)is expected to achieve clean and sustainable NH_(3)production by using clean solar energy.To date,the new photocatalysts for photocatalytic reduction of N_(2)to NH_(3)at room temperature and atmospheric pressure have not been fully developed.The major challenge is to achieve high light-absorption efficiency,conversion efficiency,and stability of photocatalysts.Herein,the methods for measuring produced NH_(3)are compared,and the problems related to possible NH_(3)pollution in photocatalytic systems are mentioned to provide accurate ideas for measuring photocatalytic efficiency.The recent progress of nitrogen reduction reaction(NRR)photocatalysts at ambient temperature and pressure is summarized by introducing charge transfer,migration,and separation in photocatalytic NRR,which provides a guidance for the selection of future photocatalyst.More importantly,we introduce the latest research strategies of photocatalysts in detail,which can guide the preparation and design of photocatalysts with high NRR activity.

Cultivation Path of Nursing Undergraduates’ Scientific Research and Innovation Ability

Objective:The cultivation of the innovation ability and scientific research is one of the nursing learning objectives for undergraduate students.To explore the method and effect of training system of scientific research innovation ability of nursing undergraduates based on“3332”.Methods:Three course learning modules are constructed:stage-based course learning module,systematic project practice training module and comprehensive practice training module.A practical training platform for scientific research innovation projects is built,and undergraduate scientific research innovation ability training is carried out from both in-class and out-of-class lines.Results:Since 2017,the students have obtained 7 national innovation and entrepreneurship training programs,52 university-level undergraduate scientific research projects,published more than 10 academic papers,and obtained 2 patent authorization.Conclusions:The training system of scientific research innovation ability of nursing undergraduates based on“3332”is conducive to the development of scientific research innovation ability of nursing students,and to cultivate nursing talents who can adapt to the development of the new era and have better post competence.

Integration of Theory and Practice in Medical Morphology Curriculum in Postgraduate Training:A Flipped Classroom and Case-based Learning Exercise

Objective:The integration of training in theory and practice across the medical education spectrum is being encouraged to increase student understanding and skills in the sciences.This study aimed to determine the deciding factors that drive students'perceived advantages in class to improve precision education and the teaching model.Methods:A mixed strategy of an existing flipped classroom(FC)and a case-based learning(CBL)model was conducted in a medical morphology curriculum for 575 postgraduate students.The subjective learning evaluation of the individuals(learning time,engagement,study interest and concentration,and professional integration)was collected and analyzed after FC-CBL model learning.Results:The results from the general evaluation showed promising results of the medical morphology in the FC-CBL model.Students felt more engaged by instructors in person and benefited in terms of time-saving,flexible arrangements,and professional improvement.Our study contributed to the FC-CBL model in Research Design in postgraduate training in 4 categories:1)advancing a guideline of precision teaching according to individual characteristics;2)revealing whether a learning background is needed for a Research Design course to guide setting up a preliminary course;3)understanding the perceived advantages and their interfaces;and 4)barriers and/or improvement to implement the FC-CBL model in the Research Design class,such as a richer description of e-learning and hands-on practice.Conclusion:Undertaking a FC-CBL combined model could be a useful addition to pedagogy for medical morphology learning in postgraduate training.

Research trends of machine learning in traditional medicine:a big-data based tenyear bibliometric analysis

Background:With the rapid development of the world’s technology,the connection and integration between traditional medicine and modern machine learning technology are increasingly close.In this study,we aimed to analyze publications on machine learning in traditional medicine by using bibliometric methods and explore global trends in the field.Methods:Relevant research on machine learning in traditional medicine extracted from the Web of Science Core Collection database.Bibliometric analysis and visualization were performed using the Bibliometrix package in R software.Global trends,source journals,authorship,and thematic keywords analysis were performed in this study.Results:From 2012 to 2022,a total of 282 publications on machine learning in traditional medicine were identified and analyzed.The average annual growth rate of the publications was 13.35%.China had the largest contribution in this field(53.9%),followed by the United States(32.6%).IEEE Access had the largest number of published articles,with a total of 15 articles.Calvin Yu-Chian Chen,Xiao-juan Hu and Jue Wang were the main researchers in this field.Shanghai University of Traditional Chinese Medicine and University of California,San Francisco were the main research institutions.Conclusion:This study provides information on research trends in machine learning in traditional medicine to better understand research hotspots and future developments in this field.According to current global trends,the number of publications in this field will gradually increase.China currently dominated the field.Applied research of machine learning techniques may be the next hot topic in this field and deserves further attention.

Research on Innovation and Entrepreneurship Programme of College Students in China:Taking Wuming Cloud Project as a Case Study

The innovation and entrepreneurship of college students is a new type of education and research model that takes cultivating students’innovative spirit and ability as the primary value orientation and takes the particular group of college students and graduated college students as the central part of entrepreneurship.In order to comply with the national innovation-driven development strategy,colleges and universities also cultivate innovative talents in line with the talent market through innovation and entrepreneurship training.Under the vital innovation and entrepreneurship atmosphere in the country and universities,we fully understand the regional situation of Nanning and Wuming in Guangxi Province and put forward the“Wuming Cloud Project”.The Wuming Cloud Project aims to create a comprehensive international ethnic and cultural park that integrates Southeast Asian flavours,traditional architecture,and ethnic cultures and attracts tourists through diversified cultural experiences,convenient transportation services,and a variety of promotional tools,which will not only promote the tourism and economic development of Wuming but also bring tourists an immersive experience of Southeast Asian ethnic cultures.The Cultural Park is significant to Nanning in absorbing resources from various parties,displaying particular cultures,and promoting tourism and economic development.

Developing Theoretical Relativistic Framework for Research in Open and Flexible Learning： A New Trend in Educational Research

The purpose of research study was to develop a theoretical relativistic framework for research in open and flexible learning environment because it is a new dimension in the field of education. Developing a theoretical relativistic framework for any research study is first and prime step in walking on the track to reach the distinction set by the researcher. Open and flexible learning is a new trend in education, enriched with ICT-use as a basic demand of the 21st century generation in all parts of the globe. So, it requires a theoretical framework for its initiation, implementation, development and evaluation which is relatively developed and advanced from the existing framework. In any research study the literature review is carried out in order to develop, build or construct a theoretical framework. The researcher of the study has observed while attending the international conference on ODL （AAOU, 2013） that most of the studies require theoretical underpinning for ICT-use in education. The researcher assume that being a new trend in education to use ICT for teaching learning purpose; it requires conceptual clarity and theoretical background of the user and researcher, because, without theory the practice is wastage of money, time and energy and it becomes ineffective and requires relatively new conceptual development. So, the problem stated by the researcher for the study was： Developing theoretical relativistic framework for research in open and flexible learning： A new trend in educational research. The objective of the study was integrating the interrelated concepts to build a pnemonological network for identifying the constructs in ICT-rich open and flexible learning environment. The study was significant because it provided theoretical background for conducting research in ICT-use for teaching and learning through open and flexible systems; whether blended or online learning and training. The methodology used by the researcher was qualitative and interpretive because there were reviewing of literature and meta-analysis for building the framework. The data were analyzed and interpreted by the researcher for the findings and drawing conclusions. On the basis of conclusions the researcher has made suggestions and recommendations for conducting research in open and flexible learning environment by using this theoretical relativistic framework. The framework was named as Virtual Learning Environment Framework （VLEF）.

An Analysis of the Research Trends in Blended Learning Methods in Teaching College English Reading Courses

Curtis J.Bonk defined blended learning as a combination of face-to-face and computer-assisted online learning instruction since it was gradually formed after the emergence of the Internet[1,2].Breen pointed out that blended learning is a learning method that combines online and offline learning activities and resources[3].The blended learning approach is popular in school and e-learning.Moreover,it is one of the important trends in promoting higher education reform in the coming years.Therefore,it has attracted the attention of international researchers[4].In this paper,42 articles in Scopus(established by international institutions)and 30 articles in CNKI(found by Chinese mainland institutions)on the query of“college English reading blended learning”in the field of education were analyzed.Furthermore,CiteSpace software was used to analyze the research hotspots and trends with the keyword clusters and citations that occurred in the last two decades(1999 to 2022)to foresee future research prospects.

A Study on the Causes of Students'Poor Learning Attitudes and the Social Psychological Countermeasures to Change Them

At this stage,with the continuous improvement of the quality of life and education,students at all levels of education are facing great pressure of learning and competition in life.If these pressures are not relieved orsolved in a timely manner,the lighter they affect daily life and learning,the more serious they cause mental health problems such as depression and anxiety,and even the horrible idea of ending their lives prematurely.Therefore,educators must pay great attention to students'learning status and mental health,and if students are found to have bad learning attitudes,they must promptly understand the causes of their balearning attitudes and,on that basis,develop and implement effective psychologicalguidance and mental health education programs to alleviate students'learning stress and mental health problems.In social psychology,students'behavior is the main influencing factor of learning mental health,behavior and mental health have a close relationship,through student behavior patterns and changes in learning attitudes can understand the psychological characteristics and health status of students.Therefore,many educators analyze the causes of students'poor learning attitudes based on socialpsychology,and develop and implement effective mental health education countermeasures to improve and transform poor learning attitudes.

Brain Research on Mental Disorders: A Criticism

Objective: To expose the problems and inherent limitations of neuroscience-based brain research on mental disorders. Method: Discussion of the theory underlying brain research on mental disorders, followed by a systematic evaluation of typical studies. Results: The fundamental problem is that brain researchers fail to differentiate between biological mental disorders in which brain processes cause the disorder (notably schizophrenia, bipolar disorder, and melancholic depression) and learned mental disorders in which brain processes mediate but do not cause the disorder (which is the case with reactive depression, reactive anxiety, OCD, and PTSD). Researchers have been unsuccessful in identifying mechanisms in the brain that cause biological mental disorders, and will never be able to locate the innumerable specific neural connections that mediate learned mental disorders. Moreover, the author’s review of typical studies in this field shows that they have serious problems with theory, measurement, and data analysis, and that their findings cannot be trusted. Conclusions: Neuroscience-based brain research on mental disorders, unlike other neurological research, has been an expensive failure and it is not worth continuing.

Using AI and Precision Nutrition to Support Brain Health during Aging

Artificial intelligence, often referred to as AI, is a branch of computer science focused on developing systems that exhibit intelligent behavior. Broadly speaking, AI researchers aim to develop technologies that can think and act in a way that mimics human cognition and decision-making [1]. The foundations of AI can be traced back to early philosophical inquiries into the nature of intelligence and thinking. However, AI is generally considered to have emerged as a formal field of study in the 1940s and 1950s. Pioneering computer scientists at the time theorized that it might be possible to extend basic computer programming concepts using logic and reasoning to develop machines capable of “thinking” like humans. Over time, the definition and goals of AI have evolved. Some theorists argued for a narrower focus on developing computing systems able to efficiently solve problems, while others aimed for a closer replication of human intelligence. Today, AI encompasses a diverse set of techniques used to enable intelligent behavior in machines. Core disciplines that contribute to modern AI research include computer science, mathematics, statistics, linguistics, psychology and cognitive science, and neuroscience. Significant AI approaches used today involve statistical classification models, machine learning, and natural language processing. Classification methods are widely applicable to problems in various domains like healthcare, such as informing diagnostic or treatment decisions based on patterns in data. Dean and Goldreich, 1998, define ML as an approach through which a computer has to learn a model by itself from the data provided but no specification on the sort of model is provided to the computer. They can then predict values for things that are different from the values used in training the models. NLP looks at two interrelated concerns, the task of training computers to understand human languages and the fact that since natural languages are so complex, they lend themselves very well to serving a number of very useful goals when used by computers.

Under "Integration of Doing, Learning and Teaching", Research on the Project-Based Teaching Innovation of "Landscape Planning and Design"

Based on the research on the project course theory of "integration of theory and practice" in higher vocational education and the analysis of practical teaching in colleges and universities at home and abroad, combined with literature research, case analysis, system theory and other research methods, the project-based teaching goal, model, content and means of "integration of doing, learning and teaching" in higher vocational education is explored, and the project-based teaching model of "Landscape Planning and Design" is discussed combined with the application of information-based teaching methods. So as to provide references for carrying out the project-based teaching in similar courses in higher vocational colleges and really achieve docking the actual post requirements with the course to provide the basis for achieving the purpose of cultivating skilled talents in higher vocational education.

Analysis and Strategy Research on the Mathematics Learning Situation of the Postgraduate Candidates

This study takes the students who intend to study for graduate students as the research object,and makes a questionnaire survey on the mathematics learning situation and learning platform of the postgraduate candidates.Questionnaires were distributed online and offline,and a total of 326 valid questionnaires were collected.Based on 326 questionnaires,this paper analyzes the current learning situation of mathematics in the postgraduate entrance examination and studies the strategies based on the present situation,which points out the direction for the construction of mathematics learning and communication platform based on the needs of postgraduate entrance examination.

Study of The Technical Index of Online Learning Behavior Analysis of Nursing Majors on The Superstar Platform Based on The Kirkpatrick Evaluation Model

Objective:To analyze the technical indexes of students’online learning behavior analysis based on Kirkman’s evaluation model,sort out the basic indexes of online learning behavior,and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis.Methods:The online learning behavior data of Physiology of nursing students from 2021-2023 and the first semester of 22 nursing classes(3 and 4)were collected and analyzed.The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation.Results:The study found that the demand for online learning of nursing students from 2021-2023 increased and the effect was statistically significant.Compared with the stage assessment results,the online learning effect was statistically significant.Conclusion:The main indicators for evaluating and classifying online learning behaviors were summarized.These two indicators can help teachers predict which part of students need learning intervention,optimize the teaching process,and help students improve their learning behavior and academic performance.

Empirical Research of Farmer College Students' Learning Ability and Learning Effect in the Digital Environment

In the course of training farmer college students,there have been a number of problems facing the modern distance education based on digital learning environment,such as weak learning adaptability and ability of farmers and diverse learning needs.Using the empirical methods of questionnaire survey and interview,this article conducts an analysis of the farmer college students' digital learning ability and learning effect,and based on the theoretical study and practical achievements,explores some aspects,such as the information literacy and entrepreneurship ability training for farmer college students,the reform of course teaching and practice teaching,and the building of digital learning platform and special resources.And finally some innovative ideas and recommendations are put forth.