Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen
Artificial intelligence (AI), a transformative technology rooted in decades of computational evolution, from early symbolic reasoning to modern deep learning breakthroughs, is bringing great impact and opportunities to scientific research. Synchronously, AI is rapidly transforming traditional approaches in bone research. The surge in orthopedic big data, advancements in high‐performance computing, as well as innovative AI algorithms, has led to an explosive growth in applications across bone fundamental research and orthopedic clinical practice. These applications span pathological investigation, biomarker discovery, screening of critical intervention targets, drug discovery, disease diagnosis, treatment assistance, postoperative rehabilitation, and prediction of disease recurrence, highlighting vast potential of AI to facilitate bone research. However, challenges persist regarding data quality, data sharing, interpretability, and ethical considerations. In the future, advances in AI are expected to drive significant progress in drug target identification and new drug discovery, moving orthopedic clinical practice from symptom management toward precision medicine. Additionally, the integration of large language models and parallel intelligence in orthopedics could bring revolutionary changes. We hope this review can provide basis for AI applications in biological research and clinical translation, advancing intelligent and personalized management of musculoskeletal system diseases.
{"title":"Artificial Intelligence for Bone: Theory, Methods, and Applications","authors":"Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen","doi":"10.1002/aidi.202500070","DOIUrl":"https://doi.org/10.1002/aidi.202500070","url":null,"abstract":"Artificial intelligence (AI), a transformative technology rooted in decades of computational evolution, from early symbolic reasoning to modern deep learning breakthroughs, is bringing great impact and opportunities to scientific research. Synchronously, AI is rapidly transforming traditional approaches in bone research. The surge in orthopedic big data, advancements in high‐performance computing, as well as innovative AI algorithms, has led to an explosive growth in applications across bone fundamental research and orthopedic clinical practice. These applications span pathological investigation, biomarker discovery, screening of critical intervention targets, drug discovery, disease diagnosis, treatment assistance, postoperative rehabilitation, and prediction of disease recurrence, highlighting vast potential of AI to facilitate bone research. However, challenges persist regarding data quality, data sharing, interpretability, and ethical considerations. In the future, advances in AI are expected to drive significant progress in drug target identification and new drug discovery, moving orthopedic clinical practice from symptom management toward precision medicine. Additionally, the integration of large language models and parallel intelligence in orthopedics could bring revolutionary changes. We hope this review can provide basis for AI applications in biological research and clinical translation, advancing intelligent and personalized management of musculoskeletal system diseases.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500070","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147897888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ChatGPT is a rapidly evolving Artificial Intelligence tool which has attracted wide interest in higher education. This study aims to provide evidence on the experiences of student teachers who have used ChatGPT for academic-educational activities. The participants were 17 Greek preschool student teachers and the data was collected via interviews. The findings indicated that positive experiences regard general benefits (e.g., fast generation of answers, ease of use, source of information), ChatGPT’s support for educational activities (planning educational practices, interventions, lesson plans), and provision of different perspectives and approaches (including strengthening children’s social skills and ICT integration). Experienced limitations-challenges include reliability, validity of information, general/vague answers (e.g., ideas for educational practices), and limited contextual understanding. Submission of multiple queries/prompts for the generation of more relevant information was experienced both as benefit and limitation. Students value and recommend ChatGPT as a useful, supportive tool for educational purposes, and highlight the necessity for enhancement of student skills and practices (e.g., to evaluate responses/output and sources of information, and ask specific queries). Implications for students, university policy and educators are discussed. Universities need to respond to AI technology changes, adopt-establish new policies and enforce sustainability.
{"title":"ChatGPT for educational-academic activities: Preschool student teachers’ experiences","authors":"Κλεοπάτρα Νικολοπούλου","doi":"10.53761/ited/1.6","DOIUrl":"https://doi.org/10.53761/ited/1.6","url":null,"abstract":"ChatGPT is a rapidly evolving Artificial Intelligence tool which has attracted wide interest in higher education. This study aims to provide evidence on the experiences of student teachers who have used ChatGPT for academic-educational activities. The participants were 17 Greek preschool student teachers and the data was collected via interviews. The findings indicated that positive experiences regard general benefits (e.g., fast generation of answers, ease of use, source of information), ChatGPT’s support for educational activities (planning educational practices, interventions, lesson plans), and provision of different perspectives and approaches (including strengthening children’s social skills and ICT integration). Experienced limitations-challenges include reliability, validity of information, general/vague answers (e.g., ideas for educational practices), and limited contextual understanding. Submission of multiple queries/prompts for the generation of more relevant information was experienced both as benefit and limitation. Students value and recommend ChatGPT as a useful, supportive tool for educational purposes, and highlight the necessity for enhancement of student skills and practices (e.g., to evaluate responses/output and sources of information, and ask specific queries). Implications for students, university policy and educators are discussed. Universities need to respond to AI technology changes, adopt-establish new policies and enforce sustainability.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://open-publishing.org/journals/index.php/ited/article/download/1223/964","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147886772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Surface‐enhanced Raman scattering (SERS) captures intrinsic vibrational signatures of biomolecules, allowing for label‐free detection with high specificity and sensitivity. This makes SERS particularly advantageous for analyzing biofluids, tissues, and cellular environments. However, spectral complexity, signal variability, and overlapping molecular signatures pose challenges in interpretation. To overcome these challenges, artificial intelligence (AI) enhances SERS analysis by automating spectral processing, improving classification, and refining imaging, enabling highly sensitive target detection, molecular interaction validation, and clinical diagnostics. This review explores AI‐enhanced SERS (AI‐SERS) applications in disease screening, biomolecular interaction analysis, and imaging‐based diagnostics, highlighting its potential for clinical translation. By leveraging AI‐driven spectral interpretation, AI‐SERS extracts molecular signatures, quantifies biomolecular interactions, and visualizes spatial distributions, providing diagnostic insights beyond conventional identification. Furthermore, we discuss key considerations for enhancing analytical reliability, optimizing spectral feature extraction, and integrating AI‐SERS into real‐world biomedical applications, outlining future directions to advance its role in medical diagnostics and therapeutic monitoring. By refining the synergy between AI and SERS, future advancements will drive innovations in next‐generation disease monitoring, drug discovery, and medical assistance.
{"title":"AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing","authors":"Seung-Ki Lee, Rowoon Park, Ho Sang Jung","doi":"10.1002/aidi.202500030","DOIUrl":"https://doi.org/10.1002/aidi.202500030","url":null,"abstract":"Surface‐enhanced Raman scattering (SERS) captures intrinsic vibrational signatures of biomolecules, allowing for label‐free detection with high specificity and sensitivity. This makes SERS particularly advantageous for analyzing biofluids, tissues, and cellular environments. However, spectral complexity, signal variability, and overlapping molecular signatures pose challenges in interpretation. To overcome these challenges, artificial intelligence (AI) enhances SERS analysis by automating spectral processing, improving classification, and refining imaging, enabling highly sensitive target detection, molecular interaction validation, and clinical diagnostics. This review explores AI‐enhanced SERS (AI‐SERS) applications in disease screening, biomolecular interaction analysis, and imaging‐based diagnostics, highlighting its potential for clinical translation. By leveraging AI‐driven spectral interpretation, AI‐SERS extracts molecular signatures, quantifies biomolecular interactions, and visualizes spatial distributions, providing diagnostic insights beyond conventional identification. Furthermore, we discuss key considerations for enhancing analytical reliability, optimizing spectral feature extraction, and integrating AI‐SERS into real‐world biomedical applications, outlining future directions to advance its role in medical diagnostics and therapeutic monitoring. By refining the synergy between AI and SERS, future advancements will drive innovations in next‐generation disease monitoring, drug discovery, and medical assistance.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/aidi.202500030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147917543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5391/ijfis.2023.23.3.336
Sultan H. Almotiri, Nadeem Mohd, A. Al Ghamdi Mohammed, Ahmad Khan Raees
{"title":"Analytic Review of Healthcare Software by Using Quantum Computing Security Techniques","authors":"Sultan H. Almotiri, Nadeem Mohd, A. Al Ghamdi Mohammed, Ahmad Khan Raees","doi":"10.5391/ijfis.2023.23.3.336","DOIUrl":"https://doi.org/10.5391/ijfis.2023.23.3.336","url":null,"abstract":"","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135031716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5391/ijfis.2023.23.3.229
Duong Thang Long
{"title":"Efficient Multi-Task CNN for Face and Facial Expression Recognition Using Residual and Dense Architectures for Application in Monitoring Online Learning","authors":"Duong Thang Long","doi":"10.5391/ijfis.2023.23.3.229","DOIUrl":"https://doi.org/10.5391/ijfis.2023.23.3.229","url":null,"abstract":"","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135031901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5391/ijfis.2023.23.3.244
Changwon Baek, Jiho Kang, SangSoo Choi
{"title":"Online Unstructured Data Analysis Models with KoBERT and Word2vec: A Study on Sentiment Analysis of Public Opinion in Korean","authors":"Changwon Baek, Jiho Kang, SangSoo Choi","doi":"10.5391/ijfis.2023.23.3.244","DOIUrl":"https://doi.org/10.5391/ijfis.2023.23.3.244","url":null,"abstract":"","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135032730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.5391/ijfis.2023.23.3.353
Bhatt Chayan, Singhal Sunita
{"title":"Hybrid Metaheuristic Technique for Optimization of Virtual Machine Placement in Cloud","authors":"Bhatt Chayan, Singhal Sunita","doi":"10.5391/ijfis.2023.23.3.353","DOIUrl":"https://doi.org/10.5391/ijfis.2023.23.3.353","url":null,"abstract":"","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135031719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"(α₁, α₂)-Cut Sets of Reliability Measures in Moore and Bilikam Lifetime Family Using the Generalized Intuitionistic Fuzzy Numbers","authors":"Roohanizadeh Zahra, Baloui Jamkhaneh Ezzatallah, Deiri Einolah","doi":"10.5391/ijfis.2023.23.3.318","DOIUrl":"https://doi.org/10.5391/ijfis.2023.23.3.318","url":null,"abstract":"","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135032072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thiti Gaketem, Pannawit Khamrot, Pongpun Julatha, Rukchart Prasertpong, and Aiyared Iampan. International Journal of Fuzzy Logic and Intelligent Systems 2023;23:294-302. https://doi.org/10.5391/IJFIS.2023.23.3.294
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：