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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice

by Giannini, Heather M, Ginestra, Jennifer C, Chivers, Corey, Draugelis, Michael, Hanish, Asaf, Schweickert, William D, Fuchs, Barry D, Meadows, Laurie, Lynch, Michael, Donnelly, Patrick J, Pavan, Kimberly, Fishman, Neil O, Hanson, 3rd, C William, Umscheid, Craig A
Published in Critical care medicine (01.11.2019)

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Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning

by Vennemann, Bernhard, Obrist, Dominik, Rösgen, Thomas
Published in PloS one (26.09.2019)

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Early diagnosis of Alzheimer’s disease and mild cognitive impairment using MRI analysis and machine learning algorithms

by Givian, Helia, Calbimonte, Jean-Paul
Published in Discover applied sciences (01.01.2025)

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Evaluation of cerebrospinal fluid proteins as potential biomarkers for early stage Parkinson’s disease diagnosis

by T. dos Santos, Marcia Cristina, Scheller, Dieter, Schulte, Claudia, Mesa, Irene R., Colman, Peter, Bujac, Sarah R., Bell, Rosie, Berteau, Caroline, Perez, Luis Tosar, Lachmann, Ingolf, Berg, Daniela, Maetzler, Walter, Nogueira da Costa, Andre
Published in PloS one (01.11.2018)

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Machine-learning algorithm incorporating capacitated sperm intracellular pH predicts conventional in vitro fertilization success in normospermic patients

by Gunderson, Stephanie Jean, Puga Molina, Lis Carmen, Spies, Nicholas, Balestrini, Paula Ania, Buffone, Mariano Gabriel, Jungheim, Emily Susan, Riley, Joan, Santi, Celia Maria
Published in Fertility and sterility (01.04.2021)

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An interpretable machine learning model for diagnosis of Alzheimer's disease

by Das, Diptesh, Ito, Junichi, Kadowaki, Tadashi, Tsuda, Koji
Published in PeerJ (San Francisco, CA) (01.03.2019)

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Diagnostic accuracy of adenosine deaminase for pleural tuberculosis in a low prevalence setting: A machine learning approach within a 7-year prospective multi-center study

by Garcia-Zamalloa, Alberto, Vicente, Diego, Arnay, Rafael, Arrospide, Arantzazu, Taboada, Jorge, Castilla-Rodríguez, Iván, Aguirre, Urko, Múgica, Nekane, Aldama, Ladislao, Aguinagalde, Borja, Jimenez, Montserrat, Bikuña, Edurne, Basauri, Miren Begoña, Alonso, Marta, Perez-Trallero, Emilio
Published in PloS one (04.11.2021)

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Explainable artificial intelligence toward usable and trustworthy computer-aided diagnosis of multiple sclerosis from Optical Coherence Tomography

by Hernandez, Monica, Ramon-Julvez, Ubaldo, Vilades, Elisa, Cordon, Beatriz, Mayordomo, Elvira, Garcia-Martin, Elena
Published in PloS one (07.08.2023)

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Utilization of deep learning to quantify fluid volume of neovascular age-related macular degeneration patients based on swept-source OCT imaging: The ONTARIO study

by Sodhi, Simrat K., Pereira, Austin, Oakley, Jonathan D., Golding, John, Trimboli, Carmelina, Russakoff, Daniel B., Choudhry, Netan
Published in PloS one (14.02.2022)

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Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples

by Rai, Shesh N., Das, Samarendra, Pan, Jianmin, Mishra, Dwijesh C., Fu, Xiao-An
Published in PloS one (30.11.2022)

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An improved machine learning pipeline for urinary volatiles disease detection: Diagnosing diabetes

by Martinez-Vernon, Andrea S., Covington, James A., Arasaradnam, Ramesh P., Esfahani, Siavash, O’Connell, Nicola, Kyrou, Ioannis, Savage, Richard S.
Published in PloS one (27.09.2018)

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Development and validation of machine learning-driven prediction model for serious bacterial infection among febrile children in emergency departments

by Lee, Bongjin, Chung, Hyun Jung, Kang, Hyun Mi, Kim, Do Kyun, Kwak, Young Ho
Published in PloS one (25.03.2022)

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Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

by Miao, Ruizhong, Badger, Taylor C., Groesch, Kathleen, Diaz-Sylvester, Paula L., Wilson, Teresa, Ghareeb, Allen, Martin, Jongjin Anne, Cregger, Melissa, Welge, Michael, Bushell, Colleen, Auvil, Loretta, Zhu, Ruoqing, Brard, Laurent, Braundmeier-Fleming, Andrea
Published in PloS one (09.01.2020)

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Intracranial pressure based decision making: Prediction of suspected increased intracranial pressure with machine learning

by Miyagawa, Tadashi, Sasaki, Minami, Yamaura, Akira
Published in PloS one (21.10.2020)

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Machine learning analysis of volatolomic profiles in breath can identify non-invasive biomarkers of liver disease: A pilot study

by Thomas, Jonathan N., Roopkumar, Joanna, Patel, Tushar
Published in PloS one (30.11.2021)

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Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer’s Disease Neuroimaging (ADNI) database

by Beltrán, Juan Felipe, Wahba, Brandon Malik, Hose, Nicole, Shasha, Dennis, Kline, Richard P.
Published in PloS one (27.07.2020)

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Prediction and classification of Alzheimer disease based on quantification of MRI deformation

by Long, Xiaojing, Chen, Lifang, Jiang, Chunxiang, Zhang, Lijuan
Published in PloS one (06.03.2017)

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The Feasibility of Early Alzheimer’s Disease Diagnosis Using a Neural Network Hybrid Platform

by Yu, Xinke, Srivastava, Siddharth, Huang, Shan, Hayden, Eric, Teplow, David, Xie, Ya-Hong
Published in Biosensors (Basel) (01.09.2022)

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Gene Expression Profiling of Bronchoalveolar Lavage Cells Preceding a Clinical Diagnosis of Chronic Lung Allograft Dysfunction

by Weigt, S. Samuel, Wang, Xiaoyan, Palchevskiy, Vyacheslav, Gregson, Aric L., Patel, Naman, DerHovanessian, Ariss, Shino, Michael Y., Sayah, David M., Birjandi, Shirin, Lynch, Joseph P., Saggar, Rajan, Ardehali, Abbas, Ross, David J., Palmer, Scott M., Elashoff, David, Belperio, John A.
Published in PloS one (19.01.2017)

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Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model

by Yao, Bihua, Yu, Xingyu, Qiu, Liannv, Gu, Er-min, Mao, Siyu, Jiang, Lei, Tong, Jijun, Wu, Jianguo
Published in PeerJ (San Francisco, CA) (20.05.2025)

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