Výsledky vyhledávání - Predicting the arrest using Random forest Algorithm*

Crime data analysis and prediction of arrest using machine learning

Autoři: Sankul, Revanth Aruva, Tejaswi Reddy Kankal, Sai Varun a další

Zdroj: World Journal of Advanced Research and Reviews. 25:498-506

Témata: Machine Learning, Predicting the arrest using Random forest Algorithm, Crime data Analysis, Statistical methods, User friendly stream lit interface, Crime Reports

Intelligent Prognosis and Severity Analysis of Coronary Artery Disease.

Autoři: J, Janani Meghana, B P, Ramu Keerthana a další

Zdroj: Procedia Computer Science. 2025, Vol. 258, p1123-1130. 8p.

Témata: Coronary artery disease, Random forest algorithms, Decision trees, Heart failure, Cardiac arrest

Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning.

Autoři: Youngnam Lee Joon-myoung Kwon Yeha Lee a další

Zdroj: Acute & Critical Care; Aug2018, Vol. 33 Issue 3, p117-120, 4p

Témata: DEEP learning, CARDIAC arrest, MACHINE learning, ELECTRONIC health records, RANDOM forest algorithms

Predicting Bone Cement Implantation Syndrome Using Artificial Intelligence Methods

Přispěvatelé: Muhammed Cagatay Engin, associate professor doctor

Zdroj: Predicting the Development of Bone Cement Implantation Syndrome in Arthroplasty Operations Using Artificial Intelligence Methods

Evaluation and Optimization of Telephone Triage Using Artificial Intelligence (AI) Models for the Detection of Demands for Time-dependent Pathology at the Emergency and Urgent Care Coordination Center (CCUE). (TrIAje Project)

Autoři: Junta de Andalucia Andaluz Health Service

Zdroj: Proyecto "trIAje": evaluación y optimización Del Triaje telefónico Mediante Modelos de Inteligencia Artificial (IA) Para la detección de Demandas Por patología Tiempo-dependiente en el Centro Coordinador de Urgencias y Emergencias (CCUE).

ECG-based pulse detection during cardiac arrest using random forest classifier.

Autoři: Elola, Andoni Aramendi, Elisabete Irusta, Unai a další

Zdroj: Medical & Biological Engineering & Computing; Feb2019, Vol. 57 Issue 2, p453-462, 10p, 4 Charts, 4 Graphs

Témata: ELECTROCARDIOGRAPHY, CARDIAC arrest, CARDIOPULMONARY resuscitation, PULSE (Heart beat), AUTOMATED external defibrillation, ALGORITHMS, HEART beat

Prediction of cardiac attack using ensemble learning.

Autoři: Eranki, Kiran L. N. Kalerua, Sai Chandu Pilli, Tejaswi a další

Zdroj: AIP Conference Proceedings; 2024, Vol. 2971 Issue 1, p1-9, 9p

Témata: MACHINE learning, DIETARY patterns, SUPPORT vector machines, K-nearest neighbor classification, FEATURE selection, RANDOM forest algorithms, DATA privacy, MYOCARDIAL infarction, HUMAN fingerprints

Machine Learning-Based Cardiac Arrest Prediction for Early Warning System.

Autoři: Chae, Minsu Gil, Hyo-Wook Cho, Nam-Jun a další

Zdroj: Mathematics (2227-7390); Jun2022, Vol. 10 Issue 12, p2049-N.PAG, 17p

Témata: CARDIAC arrest, DEEP learning, MACHINE learning, RANDOM forest algorithms, DECISION trees, LOGISTIC regression analysis, FALSE alarms

Using Machine Learning Algorithms in Medication for Cardiac Arrest Early Warning System Construction and Forecasting

Autoři: Cheng-Tse Wu Hsiao-Ko Chang Ji-Han Liu a další

Zdroj: 2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI). :1-4

Témata: 03 medical and health sciences, 0302 clinical medicine, 3. Good health

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/taai/taai2018.html#ChangWLJ18

Predicting Arrest Release Outcomes: A Comparative Analysis of Machine Learning Models

Autoři: O. P. Adebayo Ahmed Ibrahim K.T. Oyeleke

Zdroj: مجلة التربية والعلم, Vol 34, Iss 4, Pp 62-73 (2025)

Témata: predicting, comparative analysis, bias and fairness in ml, classification algorithms, bail decision prediction, Education, Science (General), Q1-390

Popis souboru: electronic resource

Relation: https://edusj.uomosul.edu.iq/index.php/edusj/article/view/49670; https://doaj.org/toc/1812-125X; https://doaj.org/toc/2664-2530

Přístupová URL adresa: https://doaj.org/article/68211770e1be43f6b3f0b9074aca1535

Random forest machine learning method outperforms prehospital National Early Warning Score for predicting one-day mortality: A retrospective study

Autoři: Jussi Pirneskoski Joonas Tamminen Antti Kallonen a další

Zdroj: Resuscitation Plus, Vol 4, Iss , Pp 100046- (2020)

Témata: Emergency medical services, Prehospital, Cardiac arrest prevention, Early warning score, National Early Warning Score, NEWS, Specialties of internal medicine, RC581-951

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666520420300461; https://doaj.org/toc/2666-5204

Přístupová URL adresa: https://doaj.org/article/629368b162684190955e9f9478bece7f

An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest

Autoři: Joon‐myoung Kwon Youngnam Lee Yeha Lee a další

Zdroj: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 7, Iss 13 (2018)

Témata: artificial intelligence, cardiac arrest, deep learning, machine learning, rapid response system, resuscitation, Diseases of the circulatory (Cardiovascular) system, RC666-701

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2047-9980

Přístupová URL adresa: https://doaj.org/article/8016cec78ea048a8976e8c8a3d8fec81

Development of early prediction model of in-hospital cardiac arrest based on laboratory parameters

Autoři: Xinhuan Ding Yingchan Wang Weiyi Ma a další

Zdroj: BioMedical Engineering OnLine, Vol 22, Iss 1, Pp 1-15 (2023)

Témata: Algorithm, In-hospital cardiac arrest (IHCA), Prediction model, Laboratory parameters, Coagulation, Rescue treatment, Medical technology, R855-855.5

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1475-925X

Přístupová URL adresa: https://doaj.org/article/3c234bef3dc04136a5831eb4415ba1e9

Prediction of In-Hospital Cardiac Arrest Using Shallow and Deep Learning.

Autoři: Chae, Minsu Han, Sangwook Gil, Hyowook a další

Zdroj: Diagnostics (2075-4418); Jul2021, Vol. 11 Issue 7, p1255, 1p

Témata: CARDIAC arrest, DEEP learning, RANDOM forest algorithms, DECISION trees, LOGISTIC regression analysis

Value of laboratory results in addition to vital signs in a machine learning algorithm to predict in-hospital cardiac arrest: A singlecenter retrospective cohort study

Autoři: Cheungpasitporn, W Ueno, R Xu, L a další

Témata: Journal Article

URL: https://hdl.handle.net/11343/251520

Predicting prognosis of endometrioid endometrial adenocarcinoma on the basis of gene expression and clinical features using Random Forest.

Autoři: Yin, Fufen Shao, Xingyang Zhao, Lijun a další

Zdroj: Oncology Letters; Aug2019, Vol. 18 Issue 2, p1597-1606, 10p

Témata: GENE expression, ADENOCARCINOMA, LOG-rank test, PROGNOSIS, RNA sequencing

Korporace: PEKING University (Beijing, China)

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea.

Autoři: Kim, Ji Woong Ha, Juhyung Kim, Taerim a další

Zdroj: Journal of Medical Internet Research. Jul2021, Vol. 23 Issue 7, pN.PAG-N.PAG. 1p. 2 Charts.

Témata: *Artificial neural networks, Prediction models, Cardiac arrest, Receiver operating characteristic curves, Random forest algorithms, Medical personnel

Geografický termín: South Korea

Targeting domestic abuse by mining police records

Autoři: Bland, Matthew Paul Ariel, Barak

Přispěvatelé: Bland, Matthew Paul Ariel, Barak

Témata: 363.2, Domestic Abuse, Police Data, Random Forest

Přístupová URL adresa: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.793089

Artificial Intelligence in Resuscitation: A Scoping Review.

Autoři: Viderman, Dmitriy Abdildin, Yerkin G. Batkuldinova, Kamila a další

Zdroj: Journal of Clinical Medicine; Mar2023, Vol. 12 Issue 6, p2254, 12p

Témata: MEDICAL personnel, ARTIFICIAL intelligence, HOSPITAL admission & discharge, EARLY death, RESUSCITATION

Using machine learning to predict neurologic injury in venovenous extracorporeal membrane oxygenation recipients: An ELSO Registry analysisCentral MessagePerspective

Autoři: Andrew Kalra, BS Preetham Bachina, BS Benjamin L. Shou, BS a další

Zdroj: JTCVS Open, Vol 21, Iss , Pp 140-167 (2024)

Témata: venovenous extracorporeal membrane oxygenation, machine learning, acute brain injury, neurologic complications, Diseases of the circulatory (Cardiovascular) system, RC666-701, Surgery, RD1-811

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666273624001736; https://doaj.org/toc/2666-2736

Přístupová URL adresa: https://doaj.org/article/f518529204da47808cef007402ab8128