{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T20:03:58Z","timestamp":1790625838571,"version":"4.1.0"},"reference-count":105,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.saa.2026.128663","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T23:36:07Z","timestamp":1787787367000},"page":"128663","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Near-infrared spectroscopy for urine-based cancer detection: a systematic characterization of the analytical challenges of a complex biofluid matrix"],"prefix":"10.1016","volume":"365","author":[{"given":"Anastasiia","family":"Latysheva","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vladimir","family":"Protoshchak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evgenii","family":"Karpushchenko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksandr","family":"Sleptsov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikhail","family":"Mosoyan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor","family":"Jahatspanian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Artyom","family":"Vasilev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vladimir","family":"Makeev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Orlova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jelena","family":"Muncan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anastasiia","family":"Surkova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.saa.2026.128663_bb0005","doi-asserted-by":"crossref","DOI":"10.1002\/bies.201900122","article-title":"Biomarkers for early cancer diagnosis: prospects for success through the lens of tumor genetics","volume":"42","author":"Dragani","year":"2020","journal-title":"BioEssays"},{"key":"10.1016\/j.saa.2026.128663_bb0010","article-title":"Biosensors based on single or multiple biomarkers for diagnosis of prostate cancer","volume":"15","author":"Teng","year":"2023","journal-title":"Biosens. Bioelectron. X"},{"key":"10.1016\/j.saa.2026.128663_bb0015","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1080\/10408347.2022.2036941","article-title":"Raman, infrared and Brillouin spectroscopies of biofluids for medical diagnostics and for detection of biomarkers","volume":"53","author":"Aitekenov","year":"2023","journal-title":"Crit. Rev. Anal. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0020","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1080\/05704928.2020.1738453","article-title":"ATR-FTIR spectroscopy as the future of diagnostics: a systematic review of the approach using bio-fluids","volume":"56","author":"Naseer","year":"2021","journal-title":"Appl. Spectrosc. Rev."},{"key":"10.1016\/j.saa.2026.128663_bb0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.talanta.2022.123327","article-title":"Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals","volume":"243","author":"Braz","year":"2022","journal-title":"Talanta"},{"key":"10.1016\/j.saa.2026.128663_bb0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.microc.2025.115589","article-title":"Approach to non-invasive screening of kidney and prostate cancer via potentiometric multisensor urine analysis and machine learning","volume":"218","author":"Yuskina","year":"2025","journal-title":"Microchem. J."},{"key":"10.1016\/j.saa.2026.128663_bb0035","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12967-023-03960-8","article-title":"Liquid biopsies: the future of cancer early detection","volume":"21","author":"Connal","year":"2023","journal-title":"J. Transl. Med."},{"key":"10.1016\/j.saa.2026.128663_bb0040","doi-asserted-by":"crossref","unstructured":"M. Herrera, C. Galindo-Pumari\u00f1o, V. Garc\u00eda-Barber\u00e1n, C. Pe\u00f1a, A snapshot of the tumor microenvironment in colorectal cancer: the liquid biopsy, Int. J. Mol. Sci. 2019, Vol. 20, Page 6016 20 (2019) 6016. Doi: https:\/\/doi.org\/10.3390\/IJMS20236016.","DOI":"10.3390\/ijms20236016"},{"key":"10.1016\/j.saa.2026.128663_bb0045","doi-asserted-by":"crossref","first-page":"1060","DOI":"10.1111\/cas.16097","article-title":"Beyond blood: advancing the frontiers of liquid biopsy in oncology and personalized medicine","volume":"115","author":"Bao","year":"2024","journal-title":"Cancer Sci."},{"key":"10.1016\/j.saa.2026.128663_bb0050","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/978-1-0716-3346-5_3","article-title":"Detection of circulating tumor DNA in plasma using targeted sequencing","volume":"2695","author":"Sun","year":"2023","journal-title":"Methods Mol. Biol."},{"key":"10.1016\/j.saa.2026.128663_bb0055","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1016\/j.annonc.2022.05.520","article-title":"ESMO recommendations on the use of circulating tumour DNA assays for patients with cancer: a report from the ESMO precision medicine working group","volume":"33","author":"Pascual","year":"2022","journal-title":"Ann. Oncol."},{"key":"10.1016\/j.saa.2026.128663_bb0060","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/978-1-0716-3346-5_11","article-title":"Cell-free DNA, MicroRNAs, proteins, and peptides as liquid biopsy biomarkers in prostate Cancer and bladder Cancer","volume":"2695","author":"Chen","year":"2023","journal-title":"Methods Mol. Biol."},{"key":"10.1016\/j.saa.2026.128663_bb0065","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/cancers13112652","article-title":"Urine as a source of liquid biopsy for Cancer","volume":"13","author":"Oshi","year":"2021","journal-title":"Cancers (Basel)."},{"key":"10.1016\/j.saa.2026.128663_bb0070","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1089\/gtmb.2018.0189","article-title":"Urine-based liquid biopsy for nonurological cancers","volume":"23","author":"Jain","year":"2019","journal-title":"Genet. Test. Mol. Biomarkers"},{"key":"10.1016\/j.saa.2026.128663_bb0075","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.saa.2016.06.048","article-title":"High wavenumber Raman spectroscopy in the characterization of urinary metabolites of normal subjects, oral premalignant and malignant patients","volume":"171","author":"Brindha","year":"2017","journal-title":"Spectrochim. Acta A Mol. Biomol. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0080","article-title":"Urinary biomarkers in cancer detection: explorations, advancements, challenges, and future directions","author":"Pan","year":"2025","journal-title":"Int. J. Surg."},{"key":"10.1016\/j.saa.2026.128663_bb0085","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10408347.2014.929487","article-title":"Current applications of chromatographic methods in the study of human body fluids for diagnosing disorders","volume":"46","author":"J\u00f3\u017awik","year":"2016","journal-title":"Crit. Rev. Anal. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0090","article-title":"Infrared spectroscopy of urine for the non-invasive detection of endometrial cancer","volume":"14","author":"Ramirez","year":"2022","journal-title":"Cancers (Basel)"},{"key":"10.1016\/j.saa.2026.128663_bb0095","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.aca.2018.04.004","article-title":"Near infrared spectroscopy: a mature analytical technique with new perspectives \u2013 a review","volume":"1026","author":"Pasquini","year":"2018","journal-title":"Anal. Chim. Acta"},{"key":"10.1016\/j.saa.2026.128663_bb0100","doi-asserted-by":"crossref","first-page":"2948","DOI":"10.3390\/molecules25122948","article-title":"Near-infrared Spectroscopy in bio-applications","volume":"25","author":"Be\u0107","year":"2020","journal-title":"Molecules"},{"key":"10.1016\/j.saa.2026.128663_bb0105","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fchem.2020.580489","article-title":"Early diagnosis of type 2 diabetes based on near-infrared Spectroscopy combined with machine learning and Aquaphotomics","volume":"8","author":"Li","year":"2020","journal-title":"Front. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0110","doi-asserted-by":"crossref","first-page":"5959","DOI":"10.1039\/C8AN01205A","article-title":"Blood-based near-infrared spectroscopy for the rapid low-cost detection of Alzheimer\u2019s disease","volume":"143","author":"Paraskevaidi","year":"2018","journal-title":"Analyst"},{"key":"10.1016\/j.saa.2026.128663_bb0115","article-title":"Determination of NIR informative wavebands for transmission non-invasive blood glucose measurement using a Fourier transform spectrometer","volume":"8","author":"Yang","year":"2018","journal-title":"AIP Adv."},{"key":"10.1016\/j.saa.2026.128663_bb0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.pdpdt.2023.103633","article-title":"Diagnostic and monitoring applications using near infrared (NIR) spectroscopy in cancer and other diseases","volume":"42","author":"Vitorino","year":"2023","journal-title":"Photodiagnosis Photodyn. Ther."},{"key":"10.1016\/j.saa.2026.128663_bb0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.jpba.2026.117422","article-title":"Plasma-based near-infrared spectroscopy combined with aquaphotomics for colorectal cancer screening","volume":"274","author":"Chen","year":"2026","journal-title":"J. Pharm. Biomed. Anal."},{"key":"10.1016\/j.saa.2026.128663_bb0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.ab.2023.115120","article-title":"Classification of multiple cancer types by combination of plasma-based near-infrared spectroscopy analysis and machine learning modeling","volume":"669","author":"Zhu","year":"2023","journal-title":"Anal. Biochem."},{"key":"10.1016\/j.saa.2026.128663_bb0135","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7717\/peerj.15895","article-title":"Urine based near-infrared spectroscopy analysis reveals a noninvasive and convenient diagnosis method for cancers: a pilot study","volume":"11","author":"Zhu","year":"2023","journal-title":"PeerJ"},{"key":"10.1016\/j.saa.2026.128663_bb0140","doi-asserted-by":"crossref","DOI":"10.1002\/cem.3600","article-title":"Near-infrared Spectroscopy and Aquaphotomics in Cancer research: a pilot study","volume":"38","author":"Surkova","year":"2024","journal-title":"J. Chemometr."},{"key":"10.1016\/j.saa.2026.128663_bb0145","doi-asserted-by":"crossref","unstructured":"H. Mark, J. Workman, Chemometrics in Spectroscopy: Revised Second Edition, Chemom. Spectrosc. Revis. Second Ed. (2021) 1\u20131057. Doi: https:\/\/doi.org\/10.1016\/C2020-0-01907-9.","DOI":"10.1016\/C2020-0-01907-9"},{"key":"10.1016\/j.saa.2026.128663_bb0150","doi-asserted-by":"crossref","unstructured":"W. Zhang, L.C. Kasun, Q.J. Wang, Y. Zheng, Z. Lin, A review of machine learning for near-infrared spectroscopy, Sensors 2022, Vol 22, 22 (2022). Doi: https:\/\/doi.org\/10.3390\/S22249764.","DOI":"10.3390\/s22249764"},{"key":"10.1016\/j.saa.2026.128663_bb0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2024.124819","article-title":"Near infrared spectroscopy (NIRS) and machine learning as a promising tandem for fast viral detection in serum microsamples: a preclinical proof of concept","volume":"322","author":"Gomez","year":"2024","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0160","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2024.124592","article-title":"Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms, Spectrochim","volume":"320","author":"Wang","year":"2024","journal-title":"Acta Part A Mol. Biomol. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0165","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1255\/jnirs.869","article-title":"Aquaphotomics: dynamic spectroscopy of aqueous and biological systems describes peculiarities of water","volume":"17","author":"Tsenkova","year":"2009","journal-title":"J. Near Infrared Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0170","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/j.talanta.2014.08.049","article-title":"On the feasibility of near infrared spectroscopy to detect contaminants in water using single salt solutions as model systems","volume":"131","author":"Gowen","year":"2015","journal-title":"Talanta"},{"key":"10.1016\/j.saa.2026.128663_bb0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.saa.2022.121378","article-title":"Aquaphotomics for monitoring of groundwater using short-wavelength near-infrared spectroscopy, Spectrochim","volume":"279","author":"Kovacs","year":"2022","journal-title":"Acta Part A Mol. Biomol. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.talanta.2024.127399","article-title":"Rapid screening of esophageal squamous cell carcinoma by near-infrared spectroscopy combined with aquaphotomics","volume":"285","author":"Lu","year":"2025","journal-title":"Talanta"},{"key":"10.1016\/j.saa.2026.128663_bb0185","doi-asserted-by":"crossref","unstructured":"A.A. Sidorova, A. V. Grigoriev, Determination of diagnostical markers of urolithiasis by capillary electrophoresis, J. Anal. Chem. 2012 675 67 (2012) 478\u2013485. Doi: https:\/\/doi.org\/10.1134\/S1061934812050115.","DOI":"10.1134\/S1061934812050115"},{"key":"10.1016\/j.saa.2026.128663_bb0190","series-title":"Multivariate Data Analysis\u2013in Pactice. An Introduction to Multivariate Data Analysis and Experimental Design","author":"Esbensen","year":"2001"},{"key":"10.1016\/j.saa.2026.128663_bb0195","doi-asserted-by":"crossref","unstructured":"P. Wold,S; Esbensen, Kim; Geladi, Principal component analysis, Chemom. Intell. Lab. Syst. 2 (1987) 37\u201352. Doi: https:\/\/doi.org\/10.1007\/978-0-387-87811-9_2.","DOI":"10.1016\/0169-7439(87)80084-9"},{"key":"10.1016\/j.saa.2026.128663_bb0200","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0169-7439(01)00155-1","article-title":"PLS-regression: a basic tool of chemometrics","volume":"58","author":"Wold","year":"2001","journal-title":"Chemom. Intel. Lab. Syst."},{"key":"10.1016\/j.saa.2026.128663_bb0205","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"10.1016\/j.saa.2026.128663_bb0210","doi-asserted-by":"crossref","unstructured":"C. Cortes, V. Vapnik, L. Saitta, Support-vector networks, Mach. Learn. 1995 203 20 (1995) 273\u2013297. Doi: https:\/\/doi.org\/10.1007\/BF00994018.","DOI":"10.1007\/BF00994018"},{"key":"10.1016\/j.saa.2026.128663_bb0215","doi-asserted-by":"crossref","first-page":"3526","DOI":"10.1039\/C8AN00599K","article-title":"Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps","volume":"143","author":"Lee","year":"2018","journal-title":"Analyst"},{"key":"10.1016\/j.saa.2026.128663_bb0220","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1366\/0003702894202201","article-title":"Standard Normal variate transformation and De-trending of near-infrared diffuse reflectance spectra","volume":"43","author":"Barnes","year":"1989","journal-title":"Appl. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0225","doi-asserted-by":"crossref","first-page":"363","DOI":"10.3389\/fchem.2018.00363","article-title":"Essentials of Aquaphotomics and its Chemometrics approaches","volume":"6","author":"Tsenkova","year":"2018","journal-title":"Front. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0230","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v036.i11","article-title":"Feature selection with the Boruta package","volume":"36","author":"Kursa","year":"2010","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0235","doi-asserted-by":"crossref","unstructured":"R. Tibshirani, Regression shrinkage and selection via the lasso, J. R. Stat. Soc. Ser. B Stat. Methodol. 58 (1996) 267\u2013288. Doi: https:\/\/doi.org\/10.1111\/J.2517-6161.1996.TB02080.X.","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"10.1016\/j.saa.2026.128663_bb0240","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","article-title":"Regularization and variable selection Via the elastic net","volume":"67","author":"Zou","year":"2005","journal-title":"J. R. Stat. Soc. Ser. B Stat Methodol."},{"key":"10.1016\/j.saa.2026.128663_bb0245","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.chemolab.2004.12.011","article-title":"Performance of some variable selection methods when multicollinearity is present","volume":"78","author":"Chong","year":"2005","journal-title":"Chemom. Intel. Lab. Syst."},{"key":"10.1016\/j.saa.2026.128663_bb0250","unstructured":"I. Guyon, A. Elisseeff, An introduction to variable and feature selection Isabelle, J. Mach. Learn. Res. 3 (2003) 1157\u20131182."},{"key":"10.1016\/j.saa.2026.128663_bb0255","series-title":"VSURF: Variable Selection Using Random Forests","author":"Genuer","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0260","series-title":"XGBoost: A scalable tree boosting system","first-page":"785","author":"Chen","year":"2016"},{"key":"10.1016\/j.saa.2026.128663_bb0265","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","article-title":"Nearest neighbor pattern classification","volume":"13","author":"Cover","year":"2006","journal-title":"IEEE Trans. Inf. Theory"},{"key":"10.1016\/j.saa.2026.128663_bb0270","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1186\/1471-2105-7-91","article-title":"Bias in error estimation when using cross-validation for model selection","volume":"7","author":"Varma","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.saa.2026.128663_bb0275","first-page":"1833","article-title":"Permutation tests for studying classifier performance","volume":"11","author":"Ojala","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.saa.2026.128663_bb0280","author":"R Core Team"},{"key":"10.1016\/j.saa.2026.128663_bb0285","first-page":"18","article-title":"Classification and regression by randomForest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"10.1016\/j.saa.2026.128663_bb0290","first-page":"1","article-title":"Feature selection with the {Boruta} package","volume":"36","author":"Witold","year":"2010","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0295","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building predictive models in R using the caret package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0300","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v033.i01","article-title":"Regularization paths for generalized linear models via coordinate descent","volume":"33","author":"Friedman","year":"2010","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0305","doi-asserted-by":"crossref","DOI":"10.1016\/j.chemolab.2020.103937","article-title":"mdatools --- R package for chemometrics","volume":"198","author":"Kucheryavskiy","year":"2020","journal-title":"Chemom. Intell. Lab. Syst."},{"key":"10.1016\/j.saa.2026.128663_bb0310","doi-asserted-by":"crossref","DOI":"10.21105\/joss.01903","article-title":"{mlr3}: a modern object-oriented machine learning framework in {R}","author":"Lang","year":"2019","journal-title":"J. Open Source Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0315","series-title":"mlr3learners: Recommended Learners for \u201cmlr3,\u201d","author":"Lang","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0320","series-title":"mlr3tuning: Hyperparameter Optimization for mlr3","author":"Becker","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0325","series-title":"bbotk: Black-Box Optimization Toolkit","author":"Becker","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0330","series-title":"Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien [R package e1071 version 1.7\u201317]","author":"Meyer","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0335","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v011.i09","article-title":"Kernlab - an S4 package for kernel methods in R","volume":"11","author":"Karatzoglou","year":"2004","journal-title":"J. Stat. Softw."},{"key":"10.1016\/j.saa.2026.128663_bb0340","series-title":"ggplot2: Elegant Graphics for Data Analysis","author":"Wickham","year":"2016"},{"key":"10.1016\/j.saa.2026.128663_bb0345","series-title":"patchwork: The Composer of Plots","author":"Pedersen","year":"2025"},{"key":"10.1016\/j.saa.2026.128663_bb0350","series-title":"Handb. Vib. Spectrosc.","first-page":"1817","article-title":"Spectra- structure correlations in the near-infrared","author":"Weyer","year":"2006"},{"key":"10.1016\/j.saa.2026.128663_bb0355","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1080\/10643389.2014.1000761","article-title":"The characterization of Feces and urine: a review of the literature to inform advanced treatment technology","volume":"45","author":"Rose","year":"2015","journal-title":"Crit. Rev. Environ. Sci. Technol."},{"key":"10.1016\/j.saa.2026.128663_bb0360","series-title":"Infrared Spectrosc. Food Qual. Anal. Control","article-title":"Data Pre-Processing","author":"Rinnan","year":"2009"},{"key":"10.1016\/j.saa.2026.128663_bb0365","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/metabo10060229","article-title":"Recommendations and best practices for standardizing the pre-analytical processing of blood and urine samples in metabolomics","volume":"10","author":"Gonz\u00e1lez-Dom\u00ednguez","year":"2020","journal-title":"Metabolites"},{"key":"10.1016\/j.saa.2026.128663_bb0370","article-title":"Mealtime, temporal, and daily variability of the human urinary and plasma metabolomes in a tightly controlled environment","volume":"9","author":"Kim","year":"2014","journal-title":"PloS One"},{"key":"10.1016\/j.saa.2026.128663_bb0375","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.1021\/ac010102n","article-title":"Studies on the structure of water using two-dimensional near-infrared correlation spectroscopy and principal component analysis","volume":"73","author":"Segtnan","year":"2001","journal-title":"Anal. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0380","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1021\/jp013436p","article-title":"Self-modeling curve resolution study of temperature-dependent near-infrared spectra of water and the investigation of water structure","volume":"106","author":"\u0160a\u0161i\u0107","year":"2002","journal-title":"J. Phys. Chem. A"},{"key":"10.1016\/j.saa.2026.128663_bb0385","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/S0308-8146(02)00583-6","article-title":"Analysis of water in food by near infrared spectroscopy","volume":"82","author":"B\u00fcning-Pfaue","year":"2003","journal-title":"Food Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0390","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1366\/0003702854250293","article-title":"Salinity determination using NIRA","volume":"39","author":"Hirschfeld","year":"1985","journal-title":"Appl. Spectrosc."},{"key":"10.1016\/j.saa.2026.128663_bb0395","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1039\/an9891400819","article-title":"Simultaneous determination of sodium hydroxide, sodium carbonate and sodium chloride concentrations in aqueous solutions by near-infrared spectrometry","volume":"114","author":"Grant","year":"1989","journal-title":"Analyst"},{"key":"10.1016\/j.saa.2026.128663_bb0400","doi-asserted-by":"crossref","first-page":"53","DOI":"10.4236\/ajac.2011.228124","article-title":"Investigation of the potential of near infrared spectroscopy for the detection and quantification of pesticides in aqueous solution","volume":"2","author":"Gowen","year":"2011","journal-title":"Am. J. Anal. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0405","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.aca.2015.09.014","article-title":"Water revealed as molecular mirror when measuring low concentrations of sugar with near infrared light","volume":"896","author":"B\u00e1z\u00e1r","year":"2015","journal-title":"Anal. Chim. Acta"},{"key":"10.1016\/j.saa.2026.128663_bb0410","doi-asserted-by":"crossref","first-page":"2742","DOI":"10.3390\/molecules24152742","article-title":"Aquaphotomics-from innovative knowledge to integrative platform in science and technology","volume":"24","author":"Muncan","year":"2019","journal-title":"Molecules"},{"key":"10.1016\/j.saa.2026.128663_bb0415","doi-asserted-by":"crossref","DOI":"10.1088\/1757-899X\/210\/1\/012014","article-title":"An efficient near infrared spectroscopy based on aquaphotomics technique for rapid determining the level of cadmium in aqueous solution","volume":"210","author":"Putra","year":"2017","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"10.1016\/j.saa.2026.128663_bb0420","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/0009-9120(95)02011-X","article-title":"Quantitation of protein, creatinine, and urea in urine by near-infrared spectroscopy","volume":"29","author":"Shaw","year":"1996","journal-title":"Clin. Biochem."},{"key":"10.1016\/j.saa.2026.128663_bb0425","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1093\/clinchem\/47.7.1279","article-title":"Near-infrared Spectroscopy for measuring urea in Hemodialysis fluids","volume":"47","author":"Eddy","year":"2001","journal-title":"Clin. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0430","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1016\/0009-9120(93)80013-K","article-title":"Near-infrared spectroscopic determination of serum total proteins, albumin, globulins, and urea","volume":"26","author":"Hall","year":"1993","journal-title":"Clin. Biochem."},{"key":"10.1016\/j.saa.2026.128663_bb0435","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1038\/srep00856","article-title":"Spectral pattern of urinary water as a biomarker of estrus in the giant panda","volume":"2","author":"Kinoshita","year":"2012","journal-title":"Sci. Rep."},{"key":"10.1016\/j.saa.2026.128663_bb0440","doi-asserted-by":"crossref","first-page":"1671","DOI":"10.1039\/c0ay00333f","article-title":"Near infrared spectroscopy of urine proves useful for estimating ovulation in giant panda (Ailuropoda melanoleuca)","volume":"2","author":"Kinoshita","year":"2010","journal-title":"Anal. Methods"},{"key":"10.1016\/j.saa.2026.128663_bb0445","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.microc.2018.03.019","article-title":"Concentration determination of inorganic acids that do not absorb near-infrared (NIR) radiation through recognizing perturbed NIR water bands by them and investigation of accuracy dependency on their acidities","volume":"139","author":"Chang","year":"2018","journal-title":"Microchem. J."},{"key":"10.1016\/j.saa.2026.128663_bb0450","doi-asserted-by":"crossref","unstructured":"S.S. Dinges, A. Hohm, L.A. Vandergrift, J. Nowak, P. Habbel, I.A. Kaltashov, L.L. Cheng, Cancer metabolomic markers in urine: evidence, techniques and recommendations, Nat. Rev. Urol. 2019 166 16 (2019) 339\u2013362. Doi: https:\/\/doi.org\/10.1038\/s41585-019-0185-3.","DOI":"10.1038\/s41585-019-0185-3"},{"key":"10.1016\/j.saa.2026.128663_bb0455","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1177\/0960336019855168","article-title":"Recent advancements in plant aquaphotomics \u2013 towards understanding of \u201cdrying without dying\u201d phenomenon and its implications","volume":"30","author":"Muncan","year":"2019","journal-title":"NIR News"},{"key":"10.1016\/j.saa.2026.128663_bb0460","doi-asserted-by":"crossref","first-page":"7885","DOI":"10.3390\/molecules27227885","article-title":"Aquaphotomic study of effects of different mixing waters on the properties of cement mortar","volume":"27","author":"Muncan","year":"2022","journal-title":"Molecules"},{"key":"10.1016\/j.saa.2026.128663_bb0465","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fnut.2022.1058173","article-title":"Aquaphotomics monitoring of strawberry fruit during cold storage \u2013 a comparison of two cooling systems","volume":"9","author":"Muncan","year":"2022","journal-title":"Front. Nutr."},{"key":"10.1016\/j.saa.2026.128663_bb0470","doi-asserted-by":"crossref","DOI":"10.3390\/foods12020258","article-title":"Aquaphotomics monitoring of lettuce freshness during cold storage","volume":"12","author":"Vitalis","year":"2023","journal-title":"Foods"},{"key":"10.1016\/j.saa.2026.128663_bb0475","doi-asserted-by":"crossref","unstructured":"P. Harvey, A. Basuita, D. Endersby, B. Curtis, A. Iacovidou, M. Walker, A systematic review of the diagnostic accuracy of prostate specific antigen, BMC Urol. 2009 91 9 (2009) 14-. Doi: https:\/\/doi.org\/10.1186\/1471-2490-9-14.","DOI":"10.1186\/1471-2490-9-14"},{"key":"10.1016\/j.saa.2026.128663_bb0480","doi-asserted-by":"crossref","unstructured":"S.W.D. Merriel, L. Pocock, E. Gilbert, S. Creavin, F.M. Walter, A. Spencer, W. Hamilton, Systematic review and meta-analysis of the diagnostic accuracy of prostate-specific antigen (PSA) for the detection of prostate cancer in symptomatic patients, BMC Med. 2022 201 20 (2022) 54-. Doi: https:\/\/doi.org\/10.1186\/S12916-021-02230-Y.","DOI":"10.1186\/s12916-021-02230-y"},{"key":"10.1016\/j.saa.2026.128663_bb0485","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s00216-007-1651-y","article-title":"Recent applications of near-infrared spectroscopy in cancer diagnosis and therapy","volume":"390","author":"Kondepati","year":"2008","journal-title":"Anal. Bioanal. Chem."},{"key":"10.1016\/j.saa.2026.128663_bb0490","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103804","article-title":"CMACF: transformer-based cross-modal attention cross-fusion model for systemic lupus erythematosus diagnosis combining Raman spectroscopy, FTIR spectroscopy, and metabolomics","volume":"61","author":"Zhou","year":"2024","journal-title":"Inf. Process. Manag."},{"key":"10.1016\/j.saa.2026.128663_bb0495","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112204","article-title":"Cross branch co-attention network multimodal models based on Raman and FTIR spectroscopy for diagnosis of multiple selected cancers","volume":"166","author":"Zhou","year":"2024","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.saa.2026.128663_bb0500","series-title":"Feasibility study of a urine glucose level monitor for home healthcare using near infrared spectroscopy","first-page":"6001","author":"Tanaka","year":"2006"},{"key":"10.1016\/j.saa.2026.128663_bb0505","series-title":"Use of artificial neural networks in near-infrared spectroscopy calibrations for predicting glucose concentration in urine","first-page":"1040","author":"Liu","year":"2008"},{"key":"10.1016\/j.saa.2026.128663_bb0510","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0009-9120(01)00198-9","article-title":"Preliminary investigation of near-infrared spectroscopic measurements of urea, creatinine, glucose, protein, and ketone in urine","volume":"34","author":"Pezzaniti","year":"2001","journal-title":"Clin. Biochem."},{"key":"10.1016\/j.saa.2026.128663_bb0515","doi-asserted-by":"crossref","first-page":"72","DOI":"10.14326\/abe.7.72","article-title":"Reagentless estimation of urea and creatinine concentrations using near-infrared spectroscopy for spot urine test of urea-to-creatinine ratio","volume":"7","author":"Suzuki","year":"2018","journal-title":"Adv. Biomed. Eng."},{"key":"10.1016\/j.saa.2026.128663_bb0520","doi-asserted-by":"crossref","first-page":"75441D","DOI":"10.1117\/12.886007","article-title":"Development of a near-infrared spectroscopic system for monitoring urine glucose level for the use of long-term home healthcare, sixth int","volume":"7544","author":"Tanaka","year":"2010","journal-title":"Symp. Precis. Eng. Meas. Instrum."},{"key":"10.1016\/j.saa.2026.128663_bb0525","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/s10329-015-0501-3","article-title":"Detection of urinary estrogen conjugates and creatinine using near infrared spectroscopy in Bornean orangutans (pongo pygmaeus)","volume":"57","author":"Kinoshita","year":"2016","journal-title":"Primates"}],"container-title":["Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386142526012345?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1386142526012345?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:34:23Z","timestamp":1790624063000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1386142526012345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":105,"alternative-id":["S1386142526012345"],"URL":"https:\/\/doi.org\/10.1016\/j.saa.2026.128663","relation":{},"ISSN":["1386-1425"],"issn-type":[{"value":"1386-1425","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Near-infrared spectroscopy for urine-based cancer detection: a systematic characterization of the analytical challenges of a complex biofluid matrix","name":"articletitle","label":"Article Title"},{"value":"Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.saa.2026.128663","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"128663"}}