A Comparative Performance Analysis of Classical and Gradient Boosting Machine Learning Algorithms for Breast Cancer Prediction

Συγγραφείς: Nanammal, V., J, Balaji Vasan R, T, Gopinath, E, Nishanth

Πηγή: 2025 Tenth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) Science Technology Engineering and Mathematics (ICONSTEM), 2025 Tenth International Conference on. :1-7 Nov, 2025

Relation: 2025 Tenth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)

Boosting machine learning algorithms for porosity prediction in sandstone gas reservoirs

Συγγραφείς: Pathan, Alamgir^{Aff1, IDs13202025021180_cor1}, Shuvo, Md. Ashiqul Islam^Aff2

Πηγή: Journal of Petroleum Exploration and Production Technology. 16(1)

A Comparative Study of Random Forest and Gradient Boosting Machine Learning Algorithms for Tumor Classification in Biomedical Images

Συγγραφείς: Radhika, K, Dhasmana, Gulshan, Almusawi, Muntather, Badhoutiya, Arti, Singh, Balpreet, Aswini, S

Πηγή: 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) Communication, Computer Sciences and Engineering (IC3SE), 2024 International Conference on. :1442-1446 May, 2024

Relation: 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE)

Bagging and boosting machine learning algorithms for modelling sensory perception from simple chemical variables: Wine mouthfeel as a case study

Συγγραφείς: Sáenz-Navajas, María-Pilar ^{a, ⁎}, Ferreira, Chelo ^b, Bastian, Susan E.P. ^c, Jeffery, David W. ^c

Πηγή: In Food Quality and Preference August 2025 129

Boosting machine learning algorithms for predicting the macroscopic material behavior of continuous fiber reinforced composite

Συγγραφείς: Aiman Tariq, Ayşe Polat, Babür Deliktaş

Πηγή: Journal of Reinforced Plastics and Composites. 45:781-799

Σύνδεσμος πρόσβασης: https://avesis.uludag.edu.tr/publication/details/709cb7a1-667f-49d3-9a75-816632e41540/oai
https://aperta.ulakbim.gov.tr/record/285565

Machine-learning-based estimation of ground-level NO2 concentrations across Southeastern Europe using multi-source satellite, reanalysis, and emission data.

Συγγραφείς: Bilgiç E; Department of Environmental Engineering, Faculty of Engineering, Dokuz Eylul University, Izmir, Türkiye. Electronic address: efem.bilgic@deu.edu.tr., Elbir T; Department of Environmental Engineering, Faculty of Engineering, Dokuz Eylul University, Izmir, Türkiye; Environmental Research and Application Center (CEVMER), Dokuz Eylul University, Izmir, Türkiye.

Πηγή: Environmental pollution (Barking, Essex : 1987) [Environ Pollut] 2026 Aug 15; Vol. 403, pp. 128461. Date of Electronic Publication: 2026 May 28.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Elsevier Applied Science Publishers Country of Publication: England NLM ID: 8804476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-6424 (Electronic) Linking ISSN: 02697491 NLM ISO Abbreviation: Environ Pollut Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Air Pollutants*/analysis , Environmental Monitoring*/methods , Nitrogen Dioxide*/analysis , Boosting Machine Learning Algorithms*, Air Pollution/statistics & numerical data ; Europe ; Satellite Imagery

A scalable Earth observation-based machine learning framework for high-resolution mapping and uncertainty assessment of climate-sensitive child health vulnerability in Bangladesh.

Συγγραφείς: Moniruzzaman M; Department of Geography and Environmental Studies, University of Rajshahi, Bangladesh. Electronic address: mzges@ru.ac.bd.

Πηγή: The Science of the total environment [Sci Total Environ] 2026 Aug 01; Vol. 1042, pp. 181919. Date of Electronic Publication: 2026 Jun 01.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0330500 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1026 (Electronic) Linking ISSN: 00489697 NLM ISO Abbreviation: Sci Total Environ Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Child Health*/statistics & numerical data , Boosting Machine Learning Algorithms* , Climate Change*, Environmental Monitoring/methods ; Humans ; Bangladesh ; Climate ; Predictive Learning Models ; Random Forest ; Uncertainty

Development of a LightGBM-based survival prediction model for major burn patients using LDH/LYM ratio as the core predictor.

Συγγραφείς: Sun N; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China., Fan H; Department of Burn and Plastic Surgery, No.971 Hospital of the People's Liberation Army Navy, Qingdao, PR China., Zhu L; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China., Yi W; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China., Zhang L; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China., Wang G; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China. Electronic address: 13023225660@163.com., Wu G; Department of Burn Surgery, Changhai Hospital, Navy Medical University, Shanghai 200433, PR China. Electronic address: 18019359841@163.com.

Πηγή: Burns : journal of the International Society for Burn Injuries [Burns] 2026 Aug; Vol. 52 (6), pp. 108022. Date of Electronic Publication: 2026 Apr 17.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 8913178 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1409 (Electronic) Linking ISSN: 03054179 NLM ISO Abbreviation: Burns Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Burns*/mortality , Burns*/blood , L-Lactate Dehydrogenase*/blood , Boosting Machine Learning Algorithms*, Biomarkers/blood ; Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Area Under Curve ; Body Surface Area ; Kaplan-Meier Estimate ; Lymphocyte Count ; Multivariate Analysis ; Prognosis ; Retrospective Studies ; ROC Curve ; Prediction Methods, Machine

An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.

Συγγραφείς: Tekeba B; Department of Pediatrics and Child Health Nursing, School of Nursing, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia. berishboss7@gmail.com., Baykemagn ND; Department of Health Informatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia., Mengesha AT; Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia., Mengstie MA; Department of Information Science, College of Informatics, University of Gondar, Gondar, Ethiopia.

Πηγή: Infectious diseases of poverty [Infect Dis Poverty] 2026 Jul 13; Vol. 15 (1). Date of Electronic Publication: 2026 Jul 13.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: BioMed Central Country of Publication: England NLM ID: 101606645 Publication Model: Electronic Cited Medium: Internet ISSN: 2049-9957 (Electronic) Linking ISSN: 20499957 NLM ISO Abbreviation: Infect Dis Poverty Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Anemia*/epidemiology , Anemia*/diagnosis , Anemia*/etiology , Malaria*/epidemiology , Malaria*/complications , Boosting Machine Learning Algorithms*, Africa South of the Sahara/epidemiology ; Child, Preschool ; Female ; Humans ; Infant ; Male ; Classification Algorithms ; Cross-Sectional Studies ; Predictive Learning Models ; Random Forest

Development and Validation of an Interpretable Machine Learning Model for Predicting 1-Year Cardiac Death After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: A Multicenter Study.

Συγγραφείς: Liu H; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China.; Department of Cardiology Heart Center, Inner Mongolia People's Hospital Hohhot China., Hu S; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China., Zhang Y; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China., Gu T; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China., Zhang J; Cardiovascular Research Institute University of California San Francisco CA USA., Wu X; Institute for Global Health Sciences University of California San Francisco CA USA., Liu X; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China., Shao X; NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology Tianjin Medical University Tianjin China., Wang L; Cardiology Department, Chest Hospital Tianjin University Tianjin China., Tse G; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China.; School of Nursing and Health Studies Hong Kong Metropolitan University Hong Kong China., Liu T; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China., Chen K; Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology The Second Hospital of Tianjin Medical University Tianjin China.

Πηγή: Journal of the American Heart Association [J Am Heart Assoc] 2026 Jul 07; Vol. 15 (13), pp. e044796. Date of Electronic Publication: 2026 Jun 23.

Τύπος έκδοσης: Journal Article; Multicenter Study; Validation Study

Στοιχεία περιοδικού: Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 101580524 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2047-9980 (Electronic) Linking ISSN: 20479980 NLM ISO Abbreviation: J Am Heart Assoc Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Myocardial Infarction*/mortality , Myocardial Infarction*/surgery , Percutaneous Coronary Intervention*/adverse effects , Percutaneous Coronary Intervention*/mortality , Boosting Machine Learning Algorithms*, China/epidemiology ; Risk Assessment/methods ; Aged ; Female ; Humans ; Male ; Middle Aged ; Predictive Learning Models ; Predictive Value of Tests ; Reproducibility of Results ; Retrospective Studies ; Risk Factors ; Time Factors

Multi-metric evaluation and parametric optimization of stochastic gradient boosting machines for genomic prediction and selection in wheat (Triticum aestivum) breeding.

Συγγραφείς: Munroe HN; Division of Plant Breeding Methodology, Department of Crop Sciences, University of Göttingen, Carl-Sprengel-Weg 1, Göttingen 37075, Lower Saxony, Germany., Osatohanmwen BE; Division of Plant Breeding Methodology, Department of Crop Sciences, University of Göttingen, Carl-Sprengel-Weg 1, Göttingen 37075, Lower Saxony, Germany.; Center for Integrated Breeding Research, University of Göttingen, Albrecht-Thaer-Weg 3, Göttingen 37075, Lower Saxony, Germany., Reza Sharifi A; Center for Integrated Breeding Research, University of Göttingen, Albrecht-Thaer-Weg 3, Göttingen 37075, Lower Saxony, Germany.; Division of Animal Breeding and Genetics, Department of Animal Sciences, University of Göttingen, Albrecht-Thaer-Weg 3, Göttingen 37075, Lower Saxony, Germany.

Πηγή: G3 (Bethesda, Md.) [G3 (Bethesda)] 2026 Jul 06; Vol. 16 (7).

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Oxford University Press Country of Publication: England NLM ID: 101566598 Publication Model: Print Cited Medium: Internet ISSN: 2160-1836 (Electronic) Linking ISSN: 21601836 NLM ISO Abbreviation: G3 (Bethesda) Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Triticum*/genetics , Genomics*/methods , Selection, Genetic* , Plant Breeding* , Boosting Machine Learning Algorithms*, Genome, Plant ; Hybridization, Genetic

Machine Learning Model for Predicting Visual Acuity Improvement After Intrastromal Corneal Ring Surgery in Patients With Keratoconus.

Συγγραφείς: Perez E; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Louissi N; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Kallel S; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Hays Q; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Bouheraoua N; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Hamrani M; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and., Chessel A; Laboratory for Optics and Biosciences (LOB), École Polytechnique, CNRS, Inserm, Institut Polytechnique de Paris, Palaiseau, France ., Borderie V; GRC 32, Transplantation et Thérapies Innovantes de La Cornée, TTIC, Hôpital National des 15-20, Sorbonne Université, Paris, France ; and.

Πηγή: Cornea [Cornea] 2026 Jul 01; Vol. 45 (7), pp. 840-850. Date of Electronic Publication: 2025 Jul 23.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 8216186 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-4798 (Electronic) Linking ISSN: 02773740 NLM ISO Abbreviation: Cornea Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Corneal Stroma*/surgery , Keratoconus*/surgery , Keratoconus*/physiopathology , Visual Acuity*/physiology , Boosting Machine Learning Algorithms* , Prostheses and Implants* , Prosthesis Implantation*, Refraction, Ocular/physiology ; Adolescent ; Adult ; Female ; Humans ; Male ; Young Adult ; Corneal Topography ; Predictive Learning Models ; Retrospective Studies

Key predictive factors of breast cancer based on race using machine learning models.

Συγγραφείς: Yin S; School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA., Nanda G; School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA., Sundararajan R; School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA. Electronic address: raji@purdue.edu.

Πηγή: Annals of epidemiology [Ann Epidemiol] 2026 Jul; Vol. 119, pp. 110080. Date of Electronic Publication: 2026 Mar 28.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Elsevier Country of Publication: United States NLM ID: 9100013 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2585 (Electronic) Linking ISSN: 10472797 NLM ISO Abbreviation: Ann Epidemiol Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Breast Neoplasms*/ethnology , Breast Neoplasms*/epidemiology , Racial Groups*/statistics & numerical data , Boosting Machine Learning Algorithms*, Mammography/statistics & numerical data ; Adult ; Aged ; Female ; Humans ; Middle Aged ; Young Adult ; Age Factors ; Bayes Theorem ; Classification Algorithms ; Incidence ; Logistic Models ; Prediction Algorithms ; Predictive Learning Models ; Risk Factors ; White

Decoding food waste behaviours among Chinese consumers: Machine learning insights into the intention-behaviour gap.

Συγγραφείς: Wang Y; College of Economics and Management, Nanjing Forestry University, Nanjing, China.

Πηγή: Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA [Waste Manag Res] 2026 Jul; Vol. 44 (7), pp. 1037-1060. Date of Electronic Publication: 2026 Feb 22.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Sage Publications Country of Publication: England NLM ID: 9881064 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1096-3669 (Electronic) NLM ISO Abbreviation: Waste Manag Res Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Boosting Machine Learning Algorithms* , Consumer Behavior* , Food Loss and Waste* , Intention*, Humans ; China ; Predictive Learning Models ; Random Forest ; East Asian People

Identifying policy-relevant traffic crash risk factors in Cheongju, South Korea using logistic regression and explainable machine learning.

Συγγραφείς: Lee EJ; Department of Statistics, Chung Buk National University, Cheongju, Chungbuk, Republic of Korea., Kim S; Department of Statistics, Chung Buk National University, Cheongju, Chungbuk, Republic of Korea.; The Korea Transport Institute, Sejong-si, Sejong, Republic of Korea., Lee HJ; Department of Statistics, Chung Buk National University, Cheongju, Chungbuk, Republic of Korea., Jhong JH; Department of Statistics, Chung Buk National University, Cheongju, Chungbuk, Republic of Korea.

Πηγή: PloS one [PLoS One] 2026 Jun 22; Vol. 21 (6), pp. e0350616. Date of Electronic Publication: 2026 Jun 22 (Print Publication: 2026).

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: 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

Ιατρικοί όροι (MeSH): Accidents, Traffic*/statistics & numerical data , Accidents, Traffic*/prevention & control , Boosting Machine Learning Algorithms*, Automobile Driving/legislation & jurisprudence ; Humans ; Logistic Models ; Predictive Learning Models ; Random Forest ; Republic of Korea ; Risk Factors

Hepatic Steatosis Severity Prediction in Nonobese Individuals: Machine Learning Model Development and Validation.

Συγγραφείς: Zhu Y; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China., Wang Y; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China., Zhang S; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China., Yang J; Department of Health Management Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China., Zhang F; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China., Liu Y; Department of Health Management Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China., Shang J; Department of Nephrology, The Second Hospital of Anhui Medical University, Hefei, Anhui, China., Zhang Y; Department of Health Management Center, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China., Wang J; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China., Liu L; Department of Hepatobiliary Surgery, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, No.96 Jinzhai Road, Hefei, Anhui, 230001, China, 86 13845159888.; Anhui Province Key Laboratory of Hepatopancreatobiliary Surgery, Hefei, Anhui, China.; Anhui Provincial Clinical Research Center for Hepatobiliary Diseases, Hefei, Anhui, China.

Πηγή: Journal of medical Internet research [J Med Internet Res] 2026 Jun 19; Vol. 28, pp. e82529. Date of Electronic Publication: 2026 Jun 19.

Τύπος έκδοσης: Journal Article; Validation Study

Στοιχεία περιοδικού: Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN: 1438-8871 (Electronic) Linking ISSN: 14388871 NLM ISO Abbreviation: J Med Internet Res Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Fatty Liver*/diagnosis , Fatty Liver*/pathology , Boosting Machine Learning Algorithms*, Adult ; Female ; Humans ; Male ; Middle Aged ; Predictive Learning Models ; Random Forest ; Severity of Illness Index ; Support Vector Machine ; Multilayer Perceptrons ; Bayes Theorem

Unveiling Hydrogen Fluoride Emission Mechanisms in Municipal Solid Waste Incineration Using a Machine Learning Approach.

Συγγραφείς: Feng X; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province/Hainan Provincial Academician Team Innovation Center/International Joint Research Center for the Control and Prevention of Environmental Pollution on Tropical Islands of Hainan Province/School of Environment Science and Engineering/School of Computer Science and Technology, Hainan University, Haikou 570228, China., Liu L; Everbright Environmental Energy (Danzhou) Co., Ltd, No.1 Guangda Environmental Protection Avenue, Nada Town, Danzhou 571754, China., Li J; Everbright Environmental Energy (Danzhou) Co., Ltd, No.1 Guangda Environmental Protection Avenue, Nada Town, Danzhou 571754, China., Ye M; School of Information Engineering, Shanghai Maritime University, Shanghai 201306, China., Mašek O; UK Biochar Research Centre, School of GeoSciences, University of Edinburgh, Alexander Crum Brown Road, Edinburgh EH9 3FF, U.K., Gouda S; Agricultural and Biosystems Engineering Department, Faculty of Agriculture, Benha University, Benha 13736, Egypt., Mohamed ElSayed Ali I; Agricultural and Biosystems Engineering Department, Faculty of Agriculture, Benha University, Benha 13736, Egypt., Chang K; Institute of Environmental Engineering, National Sun Yat-Sen University, Taiwan 80424, China., Wang X; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province/Hainan Provincial Academician Team Innovation Center/International Joint Research Center for the Control and Prevention of Environmental Pollution on Tropical Islands of Hainan Province/School of Environment Science and Engineering/School of Computer Science and Technology, Hainan University, Haikou 570228, China., Huang Q; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province/Hainan Provincial Academician Team Innovation Center/International Joint Research Center for the Control and Prevention of Environmental Pollution on Tropical Islands of Hainan Province/School of Environment Science and Engineering/School of Computer Science and Technology, Hainan University, Haikou 570228, China.

Πηγή: Environmental science & technology [Environ Sci Technol] 2026 Jun 09; Vol. 60 (22), pp. 15901-15914. Date of Electronic Publication: 2026 May 28.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: American Chemical Society Country of Publication: United States NLM ID: 0213155 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1520-5851 (Electronic) Linking ISSN: 0013936X NLM ISO Abbreviation: Environ Sci Technol Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Boosting Machine Learning Algorithms* , Incineration*, Air Pollutants ; China ; Solid Waste

Development and validation of a machine learning model for colorectal cancer status classification using NHANES data: A cross-sectional study.

Συγγραφείς: Chen J; Department of Medical Imaging, Lianjiang County General Hospital, Fuzhou, China.

Πηγή: Medicine [Medicine (Baltimore)] 2026 Jun 05; Vol. 105 (23), pp. e49114.

Τύπος έκδοσης: Journal Article; Validation Study

Στοιχεία περιοδικού: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 2985248R Publication Model: Print Cited Medium: Internet ISSN: 1536-5964 (Electronic) Linking ISSN: 00257974 NLM ISO Abbreviation: Medicine (Baltimore) Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Colorectal Neoplasms*/epidemiology , Colorectal Neoplasms*/classification , Colorectal Neoplasms*/diagnosis , Boosting Machine Learning Algorithms*, United States/epidemiology ; Aged ; Female ; Humans ; Male ; Middle Aged ; Case-Control Studies ; Classification Algorithms ; Cross-Sectional Studies ; Logistic Models ; Nutrition Surveys ; Predictive Learning Models ; Random Forest ; Support Vector Machine

Drug response profile-based machine learning enables strategic cell line and compound selection for drug development.

Συγγραφείς: Abdel-Rehim A; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, United Kingdom., Tate E; Arctoris Ltd, Abingdon, OX14 4SA, United Kingdom., Soldatova LN; Department of Mathematics, University College London, London, WC1H 0AY, United Kingdom., King RD; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, United Kingdom.; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden.; Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, 412 96, Sweden.; The Alan Turing Institute, London, NW1 2DB, United Kingdom.

Πηγή: Bioinformatics (Oxford, England) [Bioinformatics] 2026 Jun 01; Vol. 42 (6).

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Antineoplastic Agents*/pharmacology , Drug Development*/methods , Drug Discovery*/methods , Boosting Machine Learning Algorithms* , Machine Learning*, Humans ; Cell Line, Tumor

An interpretable machine learning tool for rheumatoid arthritis screening: integrating novel cellular morphological parameters with routine blood count indices.

Συγγραφείς: You L; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China., Li X; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China.; Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China., Luo R; Department of Hospital Infection Management, West China Hospital, Sichuan University, Chengdu, China., Peng C; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China., Liu Q; Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China., Sun R; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China., Zhang N; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China.; Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China., Hou J; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China.; Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China., Yang B; Department of Laboratory Medicine, West China Tianfu Hospital, Sichuan University, Chengdu, China. yangbinhx@scu.edu.cn.; Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China. yangbinhx@scu.edu.cn.

Πηγή: Clinical rheumatology [Clin Rheumatol] 2026 Jun; Vol. 45 (6), pp. 3181-3194. Date of Electronic Publication: 2026 Apr 13.

Τύπος έκδοσης: Journal Article

Στοιχεία περιοδικού: Publisher: Springer Country of Publication: Germany NLM ID: 8211469 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1434-9949 (Electronic) Linking ISSN: 07703198 NLM ISO Abbreviation: Clin Rheumatol Subsets: MEDLINE

Ιατρικοί όροι (MeSH): Arthritis, Rheumatoid*/diagnosis , Arthritis, Rheumatoid*/blood , Boosting Machine Learning Algorithms*, Biomarkers/blood ; Adult ; Female ; Humans ; Male ; Middle Aged ; Area Under Curve ; Blood Cell Count ; Predictive Learning Models ; Retrospective Studies ; Sensitivity and Specificity