Thyroid nodule classification in ultrasound imaging using deep transfer learning.

Autores: Xu Y; Department of Ultrasound, Zhejiang Rongjun Hospital, No.309 Shuangyuan Road, Jiaxing, 314001, China., Xu M; Department of Ultrasound, Zhejiang Rongjun Hospital, No.309 Shuangyuan Road, Jiaxing, 314001, China., Geng Z; Department of Ultrasound, Zhejiang Rongjun Hospital, No.309 Shuangyuan Road, Jiaxing, 314001, China., Liu J; Interventional Cancer Institute of Chinese Integrative Medicine, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200062, China. liujie_w@sina.com.; Department of Clinical Center, Jiaxing Hospital of Traditional Chinese Medicine, Jiaxing, 314001, China. liujie_w@sina.com., Meng B; Department of Ultrasound, Zhejiang Rongjun Hospital, No.309 Shuangyuan Road, Jiaxing, 314001, China. netboysky@qq.com.

Fuente: BMC cancer [BMC Cancer] 2025 Mar 25; Vol. 25 (1), pp. 544. Date of Electronic Publication: 2025 Mar 25.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100967800 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2407 (Electronic) Linking ISSN: 14712407 NLM ISO Abbreviation: BMC Cancer Subsets: MEDLINE

Términos MeSH: Thyroid Nodule*/diagnostic imaging , Thyroid Nodule*/classification , Thyroid Nodule*/pathology , Deep Learning* , Thyroid Neoplasms*/diagnostic imaging, Humans ; Ultrasonography/methods ; Retrospective Studies ; Female ; Support Vector Machine ; Male ; Middle Aged ; ROC Curve ; Adult ; Neural Networks, Computer ; Machine Learning

M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy.

Autores: Schaduangrat N; Faculty of Medical Technology, Center for Research Innovation and Biomedical Informatics, Mahidol University, Bangkok, 10700, Thailand., Chuntakaruk H; Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.; Faculty of Science, Center of Excellence in Structural and Computational Biology, Chulalongkorn University, Bangkok, 10330, Thailand.; Faculty of Medicine, Center for Artificial Intelligence in Medicine, Chulalongkorn University, Bangkok, Bangkok, 10330, Thailand., Rungrotmongkol T; Program in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok, 10330, Thailand.; Faculty of Science, Center of Excellence in Structural and Computational Biology, Chulalongkorn University, Bangkok, 10330, Thailand., Mookdarsanit P; Faculty of Science, Computer Science and Artificial Intelligence, Chandrakasem Rajabhat University, Bangkok, 10900, Thailand., Shoombuatong W; Faculty of Medical Technology, Center for Research Innovation and Biomedical Informatics, Mahidol University, Bangkok, 10700, Thailand. watshara.sho@mahidol.ac.th.

Fuente: BMC bioinformatics [BMC Bioinformatics] 2025 Apr 30; Vol. 26 (1), pp. 117. Date of Electronic Publication: 2025 Apr 30.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE

Términos MeSH: Receptors, Glucocorticoid*/antagonists & inhibitors , Receptors, Glucocorticoid*/chemistry , Machine Learning* , Drug Discovery*/methods, Humans ; Algorithms ; Computational Biology/methods ; Ensemble Learning

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

Autores: Wang K; Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China., Li Y; Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China., Liu F; Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China., Luan X; Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China., Wang X; Science Center for Future Foods, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China.; Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China.; Engineering Research Center of Ministry of Education on Food Synthetic Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China.; Jiangsu Province Engineering Research Center of Food Synthetic Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China., Zhou J; Science Center for Future Foods, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China. zhoujw1982@jiangnan.edu.cn.; Key Laboratory of Industrial Biotechnology, Ministry of Education and School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China. zhoujw1982@jiangnan.edu.cn.; Engineering Research Center of Ministry of Education on Food Synthetic Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China. zhoujw1982@jiangnan.edu.cn.; Jiangsu Province Engineering Research Center of Food Synthetic Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, Jiangsu, China. zhoujw1982@jiangnan.edu.cn.

Fuente: BMC bioinformatics [BMC Bioinformatics] 2025 Apr 18; Vol. 26 (1), pp. 108. Date of Electronic Publication: 2025 Apr 18.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE

Términos MeSH: Single-Cell Analysis*/methods , Gene Regulatory Networks* , RNA-Seq*/methods , Deep Learning*, Algorithms ; Sequence Analysis, RNA/methods ; Humans ; Machine Learning ; Computational Biology/methods ; Single-Cell Gene Expression Analysis

Anesthesia depth prediction from drug infusion history using hybrid AI.

Autores: Wang L; Department of Anesthesiology, Tianjin First Center Hospital, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China., Weng Y; Department of Anesthesiology, Tianjin First Center Hospital, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China., Yu W; Department of Anesthesiology, Tianjin First Center Hospital, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China. yzxwenliyu@163.com.

Fuente: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Apr 08; Vol. 25 (1), pp. 158. Date of Electronic Publication: 2025 Apr 08.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE

Términos MeSH: Deep Learning* , Anesthesia*/methods, Humans ; Machine Learning

Improving genetic variant identification for quantitative traits using ensemble learning-based approaches.

Autores: Sharma J; Department of Bioscience & Bioengineering, Indian Institute of Technology, Jodhpur, 342030, Rajasthan, India., Jangale V; Department of Bioscience & Bioengineering, Indian Institute of Technology, Jodhpur, 342030, Rajasthan, India., Shekhawat RS; Department of Bioscience & Bioengineering, Indian Institute of Technology, Jodhpur, 342030, Rajasthan, India., Yadav P; Department of Bioscience & Bioengineering, Indian Institute of Technology, Jodhpur, 342030, Rajasthan, India. pyadav@iitj.ac.in.; School of Artificial Intelligence and Data Science, Indian Institute of Technology, Jodhpur, 342030, Rajasthan, India. pyadav@iitj.ac.in.

Fuente: BMC genomics [BMC Genomics] 2025 Mar 12; Vol. 26 (1), pp. 237. Date of Electronic Publication: 2025 Mar 12.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE

Términos MeSH: Genome-Wide Association Study*/methods , Machine Learning* , Quantitative Trait Loci* , Quantitative Trait, Heritable* , Genetic Variation*, Humans ; Polymorphism, Single Nucleotide ; Phenotype ; Ensemble Learning

Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out.

Autores: Williams B; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.; Zoological Society of London, Regents Park, London, United Kingdom., Balvanera SM; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom., Sethi SS; Department of Life Sciences, Imperial College London, London, United Kingdom., Lamont TAC; Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom., Jompa J; Graduate School, Universitas Hasanuddin, Makassar, Indonesia., Prasetya M; MARS Sustainable Solutions, Makassar, Indonesia., Richardson L; School of Ocean Sciences, Bangor University, Askew Street, Menai Bridge, Anglesey, United Kingdom., Chapuis L; School of Biological Sciences, University of Bristol, Bristol, United Kingdom., Weschke E; School of Biological Sciences, University of Bristol, Bristol, United Kingdom., Hoey A; Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia., Beldade R; Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia.; Estación Costera de Investigaciones Marinas, Millennium Nucleus for Ecology and Conservation of Temperate Mesophotic Reef Ecosystems, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile., Mills SC; CRIOBE, PSL Research University, Moorea, French Polynesia.; Laboratoire d'Excellence 'CORAIL', Perpignan, France., Haguenauer A; CRIOBE, PSL Research University, Moorea, French Polynesia., Zuberer F; CRIOBE, PSL Research University, Moorea, French Polynesia., Simpson SD; School of Biological Sciences, University of Bristol, Bristol, United Kingdom., Curnick D; Zoological Society of London, Regents Park, London, United Kingdom., Jones KE; Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom.

Fuente: PLoS computational biology [PLoS Comput Biol] 2025 Apr 28; Vol. 21 (4), pp. e1013029. Date of Electronic Publication: 2025 Apr 28 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

Términos MeSH: Coral Reefs* , Unsupervised Machine Learning* , Artificial Intelligence*, Animals ; Acoustics ; Ecosystem ; Algorithms ; Neural Networks, Computer ; Computational Biology ; Fishes/physiology ; Machine Learning ; Environmental Monitoring/methods

Research on memory failure prediction based on ensemble learning.

Autores: Zhang P; School of Information Engineering, Wuhan University of Technology, Wuhan, China., Zhang J; School of Information Engineering, Wuhan University of Technology, Wuhan, China., Li Y; Alibaba Cloud, Shenzhen, China.

Fuente: PloS one [PLoS One] 2025 Apr 23; Vol. 20 (4), pp. e0321954. Date of Electronic Publication: 2025 Apr 23 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Machine Learning* , Memory*/physiology, Humans ; Algorithms ; Models, Theoretical ; Ensemble Learning

Deep reinforcement learning for decision making of autonomous vehicle in non-lane-based traffic environments.

Autores: Fei Y; Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-infrastructure Systems, Changsha University of Science and Technology, Changsha, China.; School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China., Xing L; Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-infrastructure Systems, Changsha University of Science and Technology, Changsha, China.; School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China., Yao L; School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China., Yang Z; School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China., Zhang Y; School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, China.

Fuente: PloS one [PLoS One] 2025 Apr 16; Vol. 20 (4), pp. e0320578. Date of Electronic Publication: 2025 Apr 16 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Deep Learning* , Decision Making* , Automobile Driving* , Automobiles*, Humans ; Computer Simulation ; Algorithms ; Reinforcement Machine Learning

Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy.

Autores: Mishra A; School of Industrial and Information Engineering, Politecnico Di Milano, Milan, Italy., Jatt V; Department of Mechanical Engineering, School of Engineering and Applied Sciences, Bennett University, Noida, Uttar Pradesh, India., Sefene EM; Department of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan., Salunkhe S; Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.; Department of Mechanical Engineering, Gazi University Faculty of Engineering, Maltepe, Ankara, Turkey., Cep R; Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, Ostrava, Czech Republic., Abouel Nasr E; Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia.

Fuente: PloS one [PLoS One] 2025 Apr 04; Vol. 20 (4), pp. e0309751. Date of Electronic Publication: 2025 Apr 04 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Alloys*/chemistry , Aluminum*/chemistry , Supervised Machine Learning*, Friction ; Temperature ; Algorithms ; Neural Networks, Computer ; Machine Learning

Domain generalization for image classification based on simplified self ensemble learning.

Autores: Qin Z; College of Information Technology, Guangxi Police College, Nanning,China., Guo X; College of Information Engineering, China Jiliang University, Hangzhou,China., Li J; College of Continuing Education, Guangxi Police College, Nanning,China., Chen Y; College of Information Technology, Guangxi Police College, Nanning,China.

Fuente: PloS one [PLoS One] 2025 Apr 04; Vol. 20 (4), pp. e0320300. Date of Electronic Publication: 2025 Apr 04 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Image Processing, Computer-Assisted*/methods , Machine Learning*, Humans ; Algorithms ; Ensemble Learning

Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model.

Autores: Zhang H; Department of Management, Zhengzhou Business University, Zhengzhou, China., Zhang W; School of Information and Mechanical and Electrical Engineering, Zhengzhou Business University, Zhengzhou, China.

Fuente: PloS one [PLoS One] 2025 Apr 03; Vol. 20 (4), pp. e0319773. Date of Electronic Publication: 2025 Apr 03 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Deep Learning* , Risk Management*/methods, Humans ; Neural Networks, Computer ; Boosting Machine Learning Algorithms

Explainable machine learning for predictive modeling of blowing snow detection and meteorological feature assessment using XGBoost-SHAP.

Autores: Wang F; School of Civil Engineering, Beijing Jiaotong University, Beijing, China.; Guoneng Shuohuang Railway Development Co., LTD, Yuanping, Shanxi Province, China., Wang X; Guoneng Shuohuang Railway Development Co., LTD, Yuanping, Shanxi Province, China., Li S; School of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province, China.

Fuente: PloS one [PLoS One] 2025 Mar 28; Vol. 20 (3), pp. e0318835. Date of Electronic Publication: 2025 Mar 28 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Snow* , Machine Learning* , Models, Theoretical*, Wind ; Forecasting ; Weather ; Temperature ; Meteorological Concepts ; Humidity ; Boosting Machine Learning Algorithms

Sustainable visions: unsupervised machine learning insights on global development goals.

Autores: García-Rodríguez A; Instituto de Física, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.; Department of Computer Science, Aalto University School of Science, Espoo, Finland.; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México., Núñez M; Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina.; Instituto de Investigaciones en Biodiversidad y Medioambiente, Universidad Nacional del Comahue, Bariloche, Argentina., Pérez MR; Instituto de Energías Renovables, Universidad Nacional Autónoma de México, Temixco, Morelos, México., Govezensky T; Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México., Barrio RA; Instituto de Física, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México., Gershenson C; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.; Department of Systems Science and Industrial Engineering Thomas J. Watson College of Engineering and Applied Science, State University of New York at Binghamton, Binghamton, New York, United States of America.; Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.; Lakeside Labs GmbH, Klagenfurt am Wörthersee, Austria., Kaski KK; Department of Computer Science, Aalto University School of Science, Espoo, Finland., Tagüeña J; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.; Instituto de Energías Renovables, Universidad Nacional Autónoma de México, Temixco, Morelos, México.

Fuente: PloS one [PLoS One] 2025 Mar 12; Vol. 20 (3), pp. e0317412. Date of Electronic Publication: 2025 Mar 12 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Sustainable Development*/trends , Unsupervised Machine Learning*, Humans ; Goals ; United Nations ; Socioeconomic Factors ; Machine Learning

Short-term cognitive learning outcomes in team-based learning: is the permanent team important?

Autores: Heber S; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria., Wagner-Menghin M; Department of Psychiatry and Psychotherapy, Clinical Division for Social Psychiatry, Medical University of Vienna, Vienna, Austria., Volf I; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria., Slak Rupnik M; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria., Schmid D; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria., Marz R; Medical University of Vienna International, Vienna, Austria., Fischer MJM; Center for Physiology and Pharmacology, Medical University of Vienna, Vienna, Austria.

Fuente: Medical education online [Med Educ Online] 2024 Dec 31; Vol. 29 (1), pp. 2397864. Date of Electronic Publication: 2024 Sep 05.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Taylor & Francis Country of Publication: United States NLM ID: 9806550 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1087-2981 (Electronic) Linking ISSN: 10872981 NLM ISO Abbreviation: Med Educ Online Subsets: MEDLINE

Términos MeSH: Group Processes* , Problem-Based Learning* , Students, Medical*/psychology , Cooperative Behavior*, Humans ; Cognition ; Education, Medical, Undergraduate/organization & administration ; Problem Solving ; Educational Measurement ; Learning

Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence.

Autores: Mochurad L; Artificial Intelligence Department, Lviv Polytechnic National University, 12 S. Bandery St, Lviv, 79013, Ukraine. lesia.i.mochurad@lpnu.ua., Babii V; Artificial Intelligence Department, Lviv Polytechnic National University, 12 S. Bandery St, Lviv, 79013, Ukraine., Boliubash Y; Artificial Intelligence Department, Lviv Polytechnic National University, 12 S. Bandery St, Lviv, 79013, Ukraine., Mochurad Y; Danylo Halytsky Lviv National Medical University, 69 Pekarska Street, Lviv, 79010, Ukraine.

Fuente: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Feb 07; Vol. 25 (1), pp. 63. Date of Electronic Publication: 2025 Feb 07.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE

Términos MeSH: Stroke*/diagnosis , Principal Component Analysis* , Artificial Intelligence* , Machine Learning*, Humans ; Risk Assessment/methods ; Boosting Machine Learning Algorithms

Comparison of Predictive Models for Keloid Recurrence Based on Machine Learning.

Autores: Hao Y; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China., Shan M; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China., Liu H; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China., Xia Y; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China., Kuang X; Peking Union Medical College, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, Beijing, China., Song K; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China., Wang Y; Department of Plastic and Cosmetic Surgery, Peking Union Medical College Hospital, Beijing, China.

Fuente: Journal of cosmetic dermatology [J Cosmet Dermatol] 2025 Feb; Vol. 24 (2), pp. e70008.

Tipo de publicación: Journal Article; Comparative Study

Información de la Revista: Publisher: Blackwell Science Country of Publication: England NLM ID: 101130964 Publication Model: Print Cited Medium: Internet ISSN: 1473-2165 (Electronic) Linking ISSN: 14732130 NLM ISO Abbreviation: J Cosmet Dermatol Subsets: MEDLINE

Términos MeSH: Postoperative Complications*/epidemiology , Recurrence* , Keloid*/complications , Keloid*/epidemiology , Keloid*/pathology , Decision Trees* , Predictive Learning Models*, Prognosis ; ROC Curve ; Machine Learning ; Humans ; Male ; Female ; Adolescent ; Adult ; Middle Aged

Detecting cardiovascular diseases using unsupervised machine learning clustering based on electronic medical records.

Autores: Hu Y; Department of Cardiology, National Clinical Research Center for Interventional Medicine, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.; Shanghai Engineering Research Center of AI Technology for Cardiopulmonary Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China., Yan H; Department of General Surgery, Center for Bariatric and Hernia Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China., Liu M; Shanghai Engineering Research Center of AI Technology for Cardiopulmonary Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.; Department of Health Management Center, Zhongshan Hospital, Fudan University, Shanghai, 200032, China., Gao J; Shanghai Xuhui Central Hospital, Zhongshan-Xuhui Hospital, Fudan University, Shanghai, 200031, China., Xie L; Shanghai Xuhui Central Hospital, Zhongshan-Xuhui Hospital, Fudan University, Shanghai, 200031, China., Zhang C; Department of Cardiology, National Clinical Research Center for Interventional Medicine, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China., Wei L; Shanghai Xuhui Central Hospital, Zhongshan-Xuhui Hospital, Fudan University, Shanghai, 200031, China., Ding Y; Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, 200032, China. dingyy@fudan.edu.cn., Jiang H; Department of Cardiology, National Clinical Research Center for Interventional Medicine, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. jianghong_@fudan.edu.cn.; Shanghai Engineering Research Center of AI Technology for Cardiopulmonary Diseases, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. jianghong_@fudan.edu.cn.

Fuente: BMC medical research methodology [BMC Med Res Methodol] 2024 Dec 19; Vol. 24 (1), pp. 309. Date of Electronic Publication: 2024 Dec 19.

Tipo de publicación: Journal Article

Información de la Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE

Términos MeSH: Electronic Health Records*/statistics & numerical data , Cardiovascular Diseases*/diagnosis , Unsupervised Machine Learning* , Bayes Theorem*, Humans ; Cluster Analysis ; Middle Aged ; Female ; Male ; Adult ; China/epidemiology ; Aged ; Machine Learning

Prediction of Perceived Exertion Ratings in National Level Soccer Players Using Wearable Sensor Data and Machine Learning Techniques.

Autores: Leppich R; Software Engineering Group, Department of Computer Science, University of Würzburg, Würzburg, Germany., Kunz P; Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Würzburg, Germany., Bauer A; Department of Computer Science, Illinois Institute of Technology, Chicago, United States of America., Kounev S; Software Engineering Group, Department of Computer Science, University of Würzburg, Würzburg, Germany., Sperlich B; Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Würzburg, Germany., Düking P; Department of Sports Science and Movement Pedagogy, Technische Universität Braunschweig, Braunschweig, Germany.

Fuente: Journal of sports science & medicine [J Sports Sci Med] 2024 Dec 01; Vol. 23 (4), pp. 744-753. Date of Electronic Publication: 2024 Dec 01 (Print Publication: 2024).

Tipo de publicación: Journal Article; Research Support, Non-U.S. Gov't

Información de la Revista: Publisher: Dept. of Sports Medicine, Medical Faculty of Uludag University Country of Publication: Turkey NLM ID: 101174629 Publication Model: eCollection Cited Medium: Internet ISSN: 1303-2968 (Electronic) Linking ISSN: 13032968 NLM ISO Abbreviation: J Sports Sci Med Subsets: MEDLINE

Términos MeSH: Soccer*/physiology , Heart Rate*/physiology , Physical Exertion*/physiology , Machine Learning* , Perception*/physiology, Humans ; Male ; Wearable Electronic Devices ; Accelerometry/instrumentation ; Accelerometry/methods ; Young Adult ; Geographic Information Systems ; Deep Learning ; Adult ; Algorithms ; Acceleration

Multi-agent deep reinforcement learning-based robotic arm assembly research.

Autores: Cao G; School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun, China., Bai J; School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun, China.

Fuente: PloS one [PLoS One] 2025 Feb 18; Vol. 20 (2), pp. e0311550. Date of Electronic Publication: 2025 Feb 18 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Robotics*/methods , Robotics*/instrumentation , Deep Learning*, Algorithms ; Humans ; Computer Simulation ; Reinforcement, Psychology ; Reinforcement Machine Learning

SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beet.

Autores: Günder M; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany., Yamati FRI; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Barreto A; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Mahlein AK; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Sifa R; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany., Bauckhage C; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany.

Fuente: PloS one [PLoS One] 2025 Feb 13; Vol. 20 (2), pp. e0318097. Date of Electronic Publication: 2025 Feb 13 (Print Publication: 2025).

Tipo de publicación: Journal Article

Información de la Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Términos MeSH: Beta vulgaris*/microbiology , Plant Diseases* , Remote Sensing Technology*/methods , Deep Learning* , Unmanned Aerial Devices*, Machine Learning ; Image Processing, Computer-Assisted/methods ; Artificial Intelligence