Treffer 121 - 140 von 1.037

Utilizing of Big Data and Predictive Analytics Capability in Crisis Management
Mohammad Atwah AL-Ma’aitah ; Mohammad Atwah AL-Ma’aitah

Agricultural Price Forecasting Using Flask Python Application
Shivesh ; Kumar, Suryansh ; Tejaswini ; et al.
Journal of Intelligent Data Analysis and Computational Statistics (p-ISSN: 3049-3056 e-ISSN: 3048-7080); Volume 1, Issue 2, (August, 2024); 37-42; 3048-7080; 3049-3056

Python Machine Learning Blueprints Ed. 2
Combs, Alexander ; Roman, Michael ; Combs, Alexander ; et al.

Dialysis Efficiency and Transporter Evaluation Computational Tool in Peritoneal Dialysis (DETECT-PD)
Ka Chun Leung, Resident Specialist
DETECT-PD -- Dialysis Efficiency and Transporter Evaluation Computational Tool in Peritoneal Dialysis
Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. No abstract available.
Szeto CC, Wong TY, Chow KM, Leung CB, Li PK. Dialysis adequacy and transport test for characterization of peritoneal transport type in Chinese peritoneal dialysis patients receiving three daily exchanges. Am J Kidney Dis. 2002 Jun;39(6):1287-99. doi: 10.1053/ajkd.2002.33405.
SPRINT Research Group; Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, Rocco MV, Reboussin DM, Rahman M, Oparil S, Lewis CE, Kimmel PL, Johnson KC, Goff DC Jr, Fine LJ, Cutler JA, Cushman WC, Cheung AK, Ambrosius WT. A Randomized Trial of Intensive versus Standard Blood-Pressure Control. N Engl J Med. 2015 Nov 26;373(22):2103-16. doi: 10.1056/NEJMoa1511939. Epub 2015 Nov 9.
Chen CA, Lin SH, Hsu YJ, Li YC, Wang YF, Chiu JS. Neural network modeling to stratify peritoneal membrane transporter in predialytic patients. Intern Med. 2006;45(9):663-4. doi: 10.2169/internalmedicine.45.1419. Epub 2006 Jun 1. No abstract available.
Gu J, Bai E, Ge C, Winograd J, Shah AD. Peritoneal equilibration testing: Your questions answered. Perit Dial Int. 2023 Sep;43(5):361-373. doi: 10.1177/08968608221133629. Epub 2022 Nov 9.
Morelle J, Stachowska-Pietka J, Oberg C, Gadola L, La Milia V, Yu Z, Lambie M, Mehrotra R, de Arteaga J, Davies S. ISPD recommendations for the evaluation of peritoneal membrane dysfunction in adults: Classification, measurement, interpretation and rationale for intervention. Perit Dial Int. 2021 Jul;41(4):352-372. doi: 10.1177/0896860820982218. Epub 2021 Feb 10.
Blake PG, Bargman JM, Brimble KS, Davison SN, Hirsch D, McCormick BB, Suri RS, Taylor P, Zalunardo N, Tonelli M; Canadian Society of Nephrology Work Group on Adequacy of Peritoneal Dialysis. Clinical Practice Guidelines and Recommendations on Peritoneal Dialysis Adequacy 2011. Perit Dial Int. 2011 Mar-Apr;31(2):218-39. doi: 10.3747/pdi.2011.00026. No abstract available.
Chen JB, Lam KK, Su YJ, Lee WC, Cheng BC, Kuo CC, Wu CH, Lin E, Wang YC, Chen TC, Liao SC. Relationship between Kt/V urea-based dialysis adequacy and nutritional status and their effect on the components of the quality of life in incident peritoneal dialysis patients. BMC Nephrol. 2012 Jun 14;13:39. doi: 10.1186/1471-2369-13-39.
Lin YL, Lee YC, Lee CC, Wu MH. Role of Peritoneal Equilibration Test in Assessing Folate Transport During Peritoneal Dialysis. J Ren Nutr. 2024 Sep;34(5):463-468. doi: 10.1053/j.jrn.2024.02.003. Epub 2024 Mar 13.
Cnossen TT, Smit W, Konings CJ, Kooman JP, Leunissen KM, Krediet RT. Quantification of free water transport during the peritoneal equilibration test. Perit Dial Int. 2009 Sep-Oct;29(5):523-7.
Twardowski ZJ. Clinical value of standardized equilibration tests in CAPD patients. Blood Purif. 1989;7(2-3):95-108. doi: 10.1159/000169582.
Bello AK, Okpechi IG, Osman MA, Cho Y, Cullis B, Htay H, Jha V, Makusidi MA, McCulloch M, Shah N, Wainstein M, Johnson DW. Epidemiology of peritoneal dialysis outcomes. Nat Rev Nephrol. 2022 Dec;18(12):779-793. doi: 10.1038/s41581-022-00623-7. Epub 2022 Sep 16.

Análisis del Rendimiento de Redes 5G utilizando Machine Learning.
Rivera, Luis Fernando
Revista Vínculos. jul-dic2023, Vol. 20 Issue 2, p68-78. 11p.

Python Machine Learning Blueprints Ed. 2
Roman, Michael ; Roman, Michael ; Combs, Alexander ; et al.

Development of a Novel Risk Prediction Tool for Emergency Department Patients Symptoms of Coronary Artery Disease
Network of Canadian Emergency Researchers (NCER) ; Canadian Emergency Department Research Network ; Canadian Instistutes of Health Research
Development of a Novel Risk Prediction Tool for Emergency Department Patients Symptoms of Coronary Artery Disease
McRae AD, Macci AJ, Holodinsky JK, Sajobi TT, Andruchow JE, Borgundvaag B, Brooks S, Cheng I, Deb S, Fok P, Kavsak PA, Graham MM, Lee J, McLeod SL, Scheuermeyer F, Thiruganasambandamoorthy V, Wiemer H, Yan JW, Hohl CM. Development of a Novel Risk-Prediction Tool for Emergency Department Patients with Symptoms of Coronary Artery Disease: A Research Study Protocol. CJC Open. 2025 Mar 26;7(6):777-783. doi: 10.1016/j.cjco.2025.03.016. eCollection 2025 Jun.

Predictive modeling for the accounts receivable of a startup applying data analysis
Universitat Politècnica de Catalunya. Departament d'Organització d'Empreses ; Woffu Job Organizer ; Martínez-Marí Agell, Carles ; et al.

Supervised Machine Learning for Predicting Length of Stay After Lumbar Arthrodesis: A Comprehensive Artificial Intelligence Approach.
Etzel CM ; Veeramani A ; Zhang AS ; et al.
Publisher: Wolters Kluwer Country of Publication: United States NLM ID: 9417468 Publication Model: Print Cited Medium: Internet ISSN: 1940-5480 (Electronic) Linking ISSN: 1067151X NLM ISO Abbreviation: J Am Acad Orthop Surg Subsets: MEDLINE

Mastering Predictive Analytics with scikit-learn and TensorFlow
Fontaine, Alan ; Fontaine, Alan ; Fontaine, Alan ; et al.

Python: Deeper Insights into Machine Learning
Raschka, Sebastian ; Julian, David ; Hearty, John ; et al.

Software AG Launches new Open Source Library for Standards-based AI, Machine Learning and Predictive Analytics
Software AG
Business Wire (English). 08/30/2018.

Python: Deeper Insights into Machine Learning
Julian, David ; Julian, David ; Hearty, John ; et al.

Training Systems Using Python Statistical Modeling
Miller, Curtis ; Miller, Curtis ; Miller, Curtis ; et al.

Dissecting the temporal dynamics of embodied collaborative learning using multimodal learning analytics.
Yan, Lixiang ; Martinez-Maldonado, Roberto ; Swiecki, Zachari ; et al.
J Educ Psychol

Building Machine Learning Models with Scikit-learn.
Open Source For You; 4/15/2025, pN.PAG-N.PAG, 1p

Exercise Of Machine Learning Using Some Python Tools And Techniques
Ertan Mustafa Geldiev ; Nayden Valkov Nenkov ; Mariana Mateeva Petrova
ISE Research Institute, CBU International Conference Proceedings. 6(0):1062-1070

BREATHE: A GeoAI-Powered Air Quality Monitoring and Forecasting System for Urban Sustainability
S. D. Adduri ; T. Ali
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-G-2025, Pp 39-46 (2025)

Agile, IoT, and AI: Revolutionizing Warehouse Tracking and Inventory Management in Supply Chain Operations
Chowdhury, Wazahat Ahmed ; Chowdhury, Wazahat Ahmed
Journal of Procurement and Supply Chain Management ; Vol. 4 No. 1 (2025): Vol 4, Issue 1; 41 - 47; 2958-4078

Agregamento e análise de dados de automóveis
Silva, João Luís Magalhães da ; Araújo, Susana Cláudia Nicola de ; REPOSITÓRIO P.PORTO
urn:tid:203733142