From images to detection: Machine learning for blood pattern classification.

Authors: Li Y; University of California, Davis, United States of America. Electronic address: ilnli@ucdavis.edu., Shen W; University of California, Irvine, United States of America. Electronic address: weinings@uci.edu.

Source: Forensic science international [Forensic Sci Int] 2025 Oct; Vol. 375, pp. 112558. Date of Electronic Publication: 2025 Jul 13.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Science Ireland Country of Publication: Ireland NLM ID: 7902034 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-6283 (Electronic) Linking ISSN: 03790738 NLM ISO Abbreviation: Forensic Sci Int Subsets: MEDLINE

MeSH Terms: Forensic Medicine*/methods , Blood Stains* , Image Processing, Computer-Assisted*/methods , Pattern Recognition, Automated* , Boosting Machine Learning Algorithms*, Crime Victims ; Humans

A study on time-series prediction and analysis of acidity of Daqu based on multivariate data fusion and KNN-Attention-LSTM-XGBoost modeling.

Authors: Yang H; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China., Xia H; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China. 13527447962@163.com., Liu S; Anhui Province Key Laboratory of Intelligent Solid-State Fermentation Technology, Bozhou, 236800, China., Chen S; Anhui Province Key Laboratory of Intelligent Solid-State Fermentation Technology, Bozhou, 236800, China., Li L; Anhui Province Key Laboratory of Intelligent Solid-State Fermentation Technology, Bozhou, 236800, China., Liao X; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China., Fei L; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China., Xie L; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China., Tian J; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China., Hu X; School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, 644000, China.; The Liquor Making Biological Technology and Application of Key Laboratory of Sichuan Province, Yibin, 644000, China.

Source: Bioprocess and biosystems engineering [Bioprocess Biosyst Eng] 2025 Sep; Vol. 48 (9), pp. 1451-1465. Date of Electronic Publication: 2025 Jun 14.

Publication Type: Journal Article

Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101088505 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1615-7605 (Electronic) Linking ISSN: 16157591 NLM ISO Abbreviation: Bioprocess Biosyst Eng Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Fermentation*, Hydrogen-Ion Concentration ; Least-Squares Analysis ; Multivariate Analysis

Fine tuned CatBoost machine learning approach for early detection of cardiovascular disease through predictive modeling.

Authors: Hamid M; Department of Computer Science, Government College Women University Sialkot, Sialkot, 51310, Pakistan., Hajjej F; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia. fshajjej@pnu.edu.sa., Alluhaidan AS; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia., Bin Mannie NW; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia.

Source: Scientific reports [Sci Rep] 2025 Aug 25; Vol. 15 (1), pp. 31199. Date of Electronic Publication: 2025 Aug 25.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Cardiovascular Diseases*/diagnosis, Female ; Humans ; Male ; Algorithms ; Early Diagnosis ; Machine Learning ; Risk Assessment

Molecular-Level Understanding of Membrane Disruption Behaviors of Antimicrobial Peptides by Gradient Boosting Algorithm-Assisted Raman Spectroscopy.

Authors: Li C; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Zhou QQ; Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing 210002, China.; Department of Radiology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing 211100, China., Yu T; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Zhang X; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Kang Z; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Zhou M; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Wang Y; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Zou X; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Wang Z; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Guo J; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Li Q; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Lu G; Department of Radiology, Jinling Hospital, Affiliated Nanjing Medical University, Nanjing 210002, China., Xie H; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China., Guo J; School of Chemistry, Chemical Engineering and Life Sciences, Wuhan University of Technology, Wuhan 430070, China.

Source: Journal of chemical information and modeling [J Chem Inf Model] 2025 Aug 25; Vol. 65 (16), pp. 8603-8613. Date of Electronic Publication: 2025 Aug 05.

Publication Type: Journal Article

Journal Info: Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE

MeSH Terms: Antimicrobial Cationic Peptides*/pharmacology , Antimicrobial Cationic Peptides*/chemistry , Antimicrobial Peptides*/pharmacology , Antimicrobial Peptides*/chemistry , Boosting Machine Learning Algorithms* , Cell Membrane*/drug effects , Cell Membrane*/metabolism , Cell Membrane*/chemistry , Spectrum Analysis, Raman*/methods, Phospholipids/chemistry ; Phospholipids/metabolism

Mixed effect gradient boosting for high-dimensional longitudinal data.

Authors: Olaniran OR; Department of Statistics, Faculty of Physical Sciences, University of Ilorin, Ilorin, Kwara State, PMB 1515, Nigeria. olaniran.or@unilorin.edu.ng.; Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom. olaniran.or@unilorin.edu.ng., Olaniran SF; Department of Statistics and Mathematical Sciences, Faculty of Pure and Applied Sciences, Kwara State University, Malete, Kwara State, PMB 1530, Nigeria., Allohibi J; Department of Mathematics, Taibah University, Faculty of Science, Al-Munawara, 42353, Saudi Arabia., Alharbi AA; Department of Mathematics, Taibah University, Faculty of Science, Al-Munawara, 42353, Saudi Arabia., Alharbi NM; Department of Mathematics, Taibah University, Faculty of Science, Al-Munawara, 42353, Saudi Arabia.

Source: Scientific reports [Sci Rep] 2025 Aug 22; Vol. 15 (1), pp. 30927. Date of Electronic Publication: 2025 Aug 22.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms*, Female ; Humans ; Pregnancy ; Algorithms ; Computer Simulation ; Longitudinal Studies ; Placenta/metabolism ; RNA/metabolism

XGBoost models based on non imaging features for the prediction of mild cognitive impairment in older adults.

Authors: Fernández-Blázquez MA; Department of Biological and Health Psychology, School of Psychology, Universidad Autónoma de Madrid, C/ Iván Pavlov, 6, Madrid, 28049, Spain. miguelangel.fernandezb@uam.es., Ruiz-Sánchez de León JM; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain., Sanz-Blasco R; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain., Verche E; Department of Psychobiology and Methodology in Behavioural Sciences, Universidad Complutense de Madrid, Madrid, Spain., Ávila-Villanueva M; Department of Biological and Health Psychology, School of Psychology, Universidad Autónoma de Madrid, C/ Iván Pavlov, 6, Madrid, 28049, Spain., Gil-Moreno MJ; Health Research Institute of the San Carlos Clinic Hospital (IdISSC), Madrid, Spain.; Neurology Department, Hospital Clínico San Carlos, Madrid, Spain., Montenegro-Peña M; Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.; Centre for the Prevention of Cognitive Impairment, Madrid Salud, Madrid City Council, Madrid, Spain., Terrón C; Nuestra Señora del Rosario University Hospital, Madrid, Spain.; Sanitas La Zarzuela University Hospital, Madrid, Spain., Fernández-García C; Cognitive Impairment Unit, Neurology Service, Sanitas La Moraleja University Hospital, Madrid, Spain., Gómez-Ramírez J; Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain.

Source: Scientific reports [Sci Rep] 2025 Aug 13; Vol. 15 (1), pp. 29732. Date of Electronic Publication: 2025 Aug 13.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Cognitive Dysfunction*/diagnosis, Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Machine Learning

Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet.

Authors: Ejiyi CJ; Network and Data Security Key Laboratory, University of Electronic Science and Technology of China, Chengdu, Sichuan, China., Qin Z; Network and Data Security Key Laboratory, University of Electronic Science and Technology of China, Chengdu, Sichuan, China., Nneji GU; Department of Computer Science and Software Engineering, Oxford Brookes College of Chengdu University of Technology, China., Monday HN; Department of Computer Science and Software Engineering, Oxford Brookes College of Chengdu University of Technology, China., Agbesi VK; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China., Ejiyi MB; Pharmacy Department, University of Nigeria Nsukka, Enugu, Nigeria., Ejiyi TU; Department of Pure and Industrial Chemistry, University of Nigeria Nsukka, Enugu, Nigeria., Bamisile OO; Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center, Chengdu University of Technology, Chengdu, China.

Source: Network (Bristol, England) [Network] 2025 Aug; Vol. 36 (3), pp. 716-748. Date of Electronic Publication: 2024 Apr 16.

Publication Type: Journal Article; Review; Research Support, Non-U.S. Gov't

Journal Info: Publisher: Informa Healthcare Country of Publication: England NLM ID: 9431867 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1361-6536 (Electronic) Linking ISSN: 0954898X NLM ISO Abbreviation: Network Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Cardiovascular Diseases*/diagnosis , Cardiovascular Diseases*/epidemiology , Deep Learning* , Random Forest*, Humans ; Computer Simulation ; Data Mining/methods ; Early Diagnosis ; Machine Learning ; Risk Assessment/methods

XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy.

Authors: Li W; Department of Surgical Oncology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.; The Third Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China., Zhou Y; Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Henan Polytechnic University (The Second People's Hospital of Jiaozuo City), Jiaozuo, Henan, China., Luo Z; Department of Surgical Oncology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.; The Third Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China., Tan M; Department of Surgical Oncology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.; The Third Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China., Yin R; Department of General Surgery Ward 1, Hospital of Ningshan County, Ankang, Shaanxi, China., Li J; Department of Surgical Oncology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.; The Third Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Source: Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2025 Jul 29; Vol. 16, pp. 1639639. Date of Electronic Publication: 2025 Jul 29 (Print Publication: 2025).

Publication Type: Journal Article

Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Thyroid Neoplasms*/diagnosis , Thyroid Neoplasms*/diagnostic imaging , Thyroid Neoplasms*/pathology , Thyroid Nodule*/diagnostic imaging , Thyroid Nodule*/pathology , Thyroid Nodule*/diagnosis, Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Precision Medicine/methods ; Retrospective Studies ; ROC Curve ; Ultrasonography/methods

Identification of Fusarium sambucinum species complex by surface-enhanced Raman spectroscopy and XGBoost algorithm.

Authors: Caramês ETS; Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, 05508-900 São Paulo, Brazil., de Moraes-Neto VF; Department of Food Science, School of Food Engineering, State University of Campinas, 13083-862 Campinas, São Paulo, Brazil., Bertozzi BG; Department of Food Science, School of Food Engineering, State University of Campinas, 13083-862 Campinas, São Paulo, Brazil., da Silva LP; Institute of Chemistry, State University of Campinas, 13083-970 Campinas, São Paulo, Brazil., Villa JEL; Institute of Chemistry, State University of Campinas, 13083-970 Campinas, São Paulo, Brazil. Electronic address: jelv@unicamp.br., Pallone JAL; Department of Food Science, School of Food Engineering, State University of Campinas, 13083-862 Campinas, São Paulo, Brazil., Rocha LO; Department of Food Science, School of Food Engineering, State University of Campinas, 13083-862 Campinas, São Paulo, Brazil., Correa B; Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, 05508-900 São Paulo, Brazil. Electronic address: correabe@usp.br.

Source: Food chemistry [Food Chem] 2025 Jul 15; Vol. 480, pp. 143848. Date of Electronic Publication: 2025 Mar 12.

Publication Type: Journal Article; Evaluation Study

Journal Info: Publisher: Elsevier Applied Science Publishers Country of Publication: England NLM ID: 7702639 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-7072 (Electronic) Linking ISSN: 03088146 NLM ISO Abbreviation: Food Chem Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Fusarium*/chemistry , Fusarium*/classification , Fusarium*/isolation & purification , Spectrum Analysis, Raman*/methods, Hordeum/microbiology

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

Authors: Jiang Y; Department of Nursing, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032, China., Wang HW; Shanxi Medical University, Taiyuan, 030000, China., Tian FY; Department of Hospital Infection, The Second Hospital of Shanxi Medical University, Taiyuan, 030000, China., Guo Y; Department of Nursing, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032, China., Wang XM; Department of Nursing, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032, China. shiwang_0405@qq.com.

Source: Scientific reports [Sci Rep] 2025 Jun 05; Vol. 15 (1), pp. 19737. Date of Electronic Publication: 2025 Jun 05.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Carbapenems*/pharmacology , Carbapenems*/therapeutic use , Cross Infection*/microbiology , Cross Infection*/epidemiology , Drug Resistance, Bacterial* , Pseudomonas aeruginosa*/drug effects , Pseudomonas Infections*/epidemiology , Pseudomonas Infections*/microbiology , Pseudomonas Infections*/drug therapy, Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Anti-Bacterial Agents/pharmacology ; Anti-Bacterial Agents/therapeutic use ; Machine Learning ; Risk Factors ; ROC Curve

MCD-LightGBM System for Intelligent Analyzing Heterogeneous Clinical Drug Therapeutic Effects.

Authors: Yang XH, Liao HJ, Sun PY, Ma J, Wang B, He Y, Xue LG, Su LM, Wang BJ

Source: IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2025 Jun; Vol. 29 (6), pp. 3894-3905.

Publication Type: Journal Article

Journal Info: Publisher: Institute of Electrical and Electronics Engineers Country of Publication: United States NLM ID: 101604520 Publication Model: Print Cited Medium: Internet ISSN: 2168-2208 (Electronic) Linking ISSN: 21682194 NLM ISO Abbreviation: IEEE J Biomed Health Inform Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Drug Therapy*, Humans ; Algorithms ; Machine Learning

Interpretable machine learning for thyroid cancer recurrence predicton: Leveraging XGBoost and SHAP analysis.

Authors: Schindele A; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Krebold A; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Heiß U; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Nimptsch K; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Pfaehler E; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Berr C; Internal Medicine I, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Bundschuh RA; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Wendler T; Diagnostic and Interventional Radiology, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Kertels O; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Tran-Gia J; Department of Nuclear Medicine, University Hospital Würzburg, Oberdürrbacherstr. 6, Würzburg 97080, Germany., Pfob CH; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany., Lapa C; Nuclear Medicine, Faculty of Medicine, University of Augsburg, Augsburg, Germany. Electronic address: Constantin.lapa@uk-augsburg.de.

Source: European journal of radiology [Eur J Radiol] 2025 May; Vol. 186, pp. 112049. Date of Electronic Publication: 2025 Mar 14.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Science Ireland Ltd Country of Publication: Ireland NLM ID: 8106411 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7727 (Electronic) Linking ISSN: 0720048X NLM ISO Abbreviation: Eur J Radiol Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Neoplasm Recurrence, Local*/epidemiology , Neoplasm Recurrence, Local*/diagnosis , Thyroid Neoplasms*/epidemiology , Thyroid Neoplasms*/diagnosis , Thyroid Neoplasms*/diagnostic imaging, Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Biomarkers, Tumor/blood ; Germany/epidemiology ; Machine Learning ; Prognosis ; Reproducibility of Results ; Retrospective Studies ; Risk Assessment ; Risk Factors ; Sensitivity and Specificity

Prediction of cardiovascular disease based on multiple feature selection and improved PSO-XGBoost model.

Authors: Cao K; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China.; Key Laboratory of Intelligent Technology of Chemical Process Industry in Liaoning Province, Shenyang, 110142, China., Liu C; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China., Yang S; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China., Zhang Y; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China., Li L; Shenyang Maternity and Child Health Hospital, Shenyang, 110014, China., Jung H; Computer Engineering Dept, Paichai University, Daejeon, 35345, Korea. hkjung@pcu.ac.kr., Zhang S; College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, 110142, China. syzs1210@163.com.

Source: Scientific reports [Sci Rep] 2025 Apr 11; Vol. 15 (1), pp. 12406. Date of Electronic Publication: 2025 Apr 11.

Publication Type: Evaluation Study; Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Cardiovascular Diseases*/diagnosis , Cardiovascular Diseases*/epidemiology, Humans ; Area Under Curve ; ROC Curve

Analysis of the 50-mile ultramarathon distance using a predictive XGBoost model.

Authors: Turnwald J; Centre for Rehabilitation and Sports Medicine, University Hospital Bern, Inselspital Bern, University of Bern, Bern, Switzerland., Valero D; Ultra Sports Science Foundation, Pierre-Benite, France., Forte P; Higher Institute of Educational Sciences of the Douro, Penafiel, Portugal., Weiss K; Institute of Primary Care, University of Zurich, Zurich, Switzerland., Villiger E; Institute of Primary Care, University of Zurich, Zurich, Switzerland., Thuany M; Faculty of Sports, University of Porto, Porto, Portugal., Scheer V; Ultra Sports Science Foundation, Pierre-Benite, France., Wilhelm M; Centre for Rehabilitation and Sports Medicine, University Hospital Bern, Inselspital Bern, University of Bern, Bern, Switzerland., Andrade M; Physiology Department, Federal University of Sao Paulo, Sao Paulo, Brazil., Cuk I; Faculty of Sport and Physical Education, University of Belgrade, Belgrade, Serbia., Nikolaidis PT; School of Health and Caring Sciences, University of West Attica, Athens, Greece., Knechtle B; Institute of Primary Care, University of Zurich, Zurich, Switzerland. beat.knechtle@hispeed.ch.; Medbase St. Gallen Am Vadianplatz, Vadianstrasse 26, 9001, St. Gallen, Switzerland. beat.knechtle@hispeed.ch.

Source: Scientific reports [Sci Rep] 2025 Mar 15; Vol. 15 (1), pp. 9016. Date of Electronic Publication: 2025 Mar 15.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Athletic Performance*/physiology , Boosting Machine Learning Algorithms* , Marathon Running*/physiology, Adult ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Age Factors ; Algorithms ; Athletes ; Machine Learning ; Running

Global or local modeling for XGBoost in geospatial studies upon simulated data and German COVID-19 infection forecasting.

Authors: Cheng X; Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, 10587, Berlin, Germany. ximeng.cheng@hhi.fraunhofer.de., Ma J; Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, 10587, Berlin, Germany.

Source: Scientific reports [Sci Rep] 2025 Mar 14; Vol. 15 (1), pp. 8858. Date of Electronic Publication: 2025 Mar 14.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , COVID-19*/epidemiology , Forecasting*/methods, Humans ; Artificial Intelligence ; Computer Simulation ; Germany/epidemiology ; Machine Learning ; Models, Statistical ; SARS-CoV-2/isolation & purification

On QSPR analysis of glaucoma drugs using machine learning with XGBoost and regression models.

Authors: Huang L; Department of Rehabilitation Medicine, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China. Electronic address: 14736050709@163.com., Alhulwah KH; Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11623, Saudi Arabia. Electronic address: khalhulwah@imamu.edu.sa., Hanif MF; Department of Mathematics and Statistics, The University of Lahore, Lahore Campus, Pakistan. Electronic address: farhanlums@gmail.com., Siddiqui MK; Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Pakistan. Electronic address: kamransiddiqui75@gmail.com., Ikram AS; Department of Mathematics and Statistics, The University of Lahore, Lahore Campus, Pakistan. Electronic address: ambar.ikram@math.uol.edu.pk.

Source: Computers in biology and medicine [Comput Biol Med] 2025 Mar; Vol. 187, pp. 109731. Date of Electronic Publication: 2025 Jan 28.

Publication Type: Journal Article

Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Glaucoma*/drug therapy , Quantitative Structure-Activity Relationship*, Humans ; Algorithms ; Machine Learning

Application of an improved LightGBM hybrid integration model combining gradient harmonization and Jacobian regularization for breast cancer diagnosis.

Authors: Sun X; Obstetrics and Gynecology, Jinan Maternity and Child Care Hospital, Jinan, 250000, Shandong, China. drsxy0302@163.com.

Source: Scientific reports [Sci Rep] 2025 Jan 20; Vol. 15 (1), pp. 2569. Date of Electronic Publication: 2025 Jan 20.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Breast Neoplasms*/diagnosis, Female ; Humans ; Data Mining/methods

Forecasting Mortality Associated Emergency Department Crowding with LightGBM and Time Series Data.

Authors: Nevanlinna J; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. jalmari.nevanlinna@tuni.fi., Eidstø A; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Emergency Department, Tampere University Hospital, Tampere, Finland., Ylä-Mattila J; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Emergency Department, Tampere University Hospital, Tampere, Finland., Koivistoinen T; Kanta-Häme Central Hospital, Hämeenlinna, Finland., Oksala N; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Centre for Vascular Surgery and Interventional Radiology, Tampere University Hospital, Tampere, Finland., Kanniainen J; Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland., Palomäki A; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Kanta-Häme Central Hospital, Hämeenlinna, Finland., Roine A; Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.

Source: Journal of medical systems [J Med Syst] 2025 Jan 15; Vol. 49 (1), pp. 9. Date of Electronic Publication: 2025 Jan 15.

Publication Type: Journal Article

Journal Info: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 7806056 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-689X (Electronic) Linking ISSN: 01485598 NLM ISO Abbreviation: J Med Syst Subsets: MEDLINE

MeSH Terms: Boosting Machine Learning Algorithms* , Crowding* , Emergency Service, Hospital*/statistics & numerical data , Forecasting*/methods , Hospital Mortality*/trends, Humans ; Bed Occupancy/statistics & numerical data ; Retrospective Studies ; Time Factors ; Weather

Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient-nurse verbal communications in home healthcare settings?

Authors: Scroggins JK; Columbia University School of Nursing, New York, New York, USA., Topaz M; Columbia University School of Nursing, New York, New York, USA.; Data Science Institute, Columbia University, New York, New York, USA.; Center for Home Care Policy & Research, VNS Health, New York, New York, USA., Song J; University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA., Zolnoori M; Columbia University School of Nursing, New York, New York, USA.; Center for Home Care Policy & Research, VNS Health, New York, New York, USA.

Source: Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing [J Nurs Scholarsh] 2025 Jan; Vol. 57 (1), pp. 47-58. Date of Electronic Publication: 2024 Jul 03.

Publication Type: Journal Article

Journal Info: Publisher: Wiley Country of Publication: United States NLM ID: 100911591 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1547-5069 (Electronic) Linking ISSN: 15276546 NLM ISO Abbreviation: J Nurs Scholarsh Subsets: MEDLINE

MeSH Terms: Nurses*/psychology , Nurses*/statistics & numerical data , Data Analysis* , Boosting Machine Learning Algorithms* , Home Health Nursing*/statistics & numerical data , Nurse-Patient Relations*, Communication ; Sound Recordings/statistics & numerical data ; United States ; Humans ; Male ; Female ; Aged ; Large Language Models

Using XGBoost and memetic programming to identify hotspots of sediment plastic pollution.

Authors: Shiwomeh DN; Department of Urban Management, Graduate School of Engineering, Kyoto University, Kyoto, 612-8133, Japan; Disaster Prevention Research Institute (DPRI), Kyoto University, Kyoto, 611-0011, Japan. Electronic address: shiwomeh.ndre.38e@st.kyoto-u.ac.jp., Kantoush SA; Disaster Prevention Research Institute (DPRI), Kyoto University, Kyoto, 611-0011, Japan. Electronic address: kantoush.samehahmed.2n@kyoto-u.ac.jp., Saber M; Disaster Prevention Research Institute (DPRI), Kyoto University, Kyoto, 611-0011, Japan. Electronic address: mohamedmd.saber.3u@kyoto-u.ac.jp., Sumi T; Disaster Prevention Research Institute (DPRI), Kyoto University, Kyoto, 611-0011, Japan. Electronic address: sumi.tetsuya.2s@kyoto-u.ac.jp., Fantong WY; Center of Research for Water and Climate Change, Institute of Geological and Mining Research (IRGM), P.O. Box 4110, Yaoundé, Cameroon. Electronic address: fantongy@gmail.com., Quang Nguyen B; The University of Danang - University of Science and Technology, 54 Nguyen Luong Bang, Danang, Viet Nam. Electronic address: nqbinh@dut.udn.vn., Abdrabo KI; Faculty of Urban and Regional Planning, Cairo University, Giza, 12613, Egypt. Electronic address: m.karim.ibrahim@cu.edu.eg., Mabrouk E; College of Engineering and Technology, American University of the Middle East, Kuwait. Electronic address: emad.mabrouk@aum.edu.kw.

Source: Environmental pollution (Barking, Essex : 1987) [Environ Pollut] 2025 Dec 15; Vol. 387, pp. 127329. Date of Electronic Publication: 2025 Oct 30.

Publication Type: Journal Article

Journal Info: 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

MeSH Terms: Plastics*/analysis , Environmental Monitoring*/methods , Geologic Sediments*/chemistry , Environmental Pollution*/statistics & numerical data, Cameroon ; Algorithms ; Boosting Machine Learning Algorithms