Suchergebnisse - "Healthcare Analytics"

Enhancing primary care quality improvement through national data collection and validation: the primary care quality initiative in Sweden

Autoren: Mansson, Jorgen Andre, Malin Johansson, Emil et al.

Quelle: Scandinavian Journal of Primary Health Care.

Schlagwörter: Primary care, quality improvement, quality indicators, data collection, validation, healthcare analytics, electronic health record

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-213445
https://doi.org/10.1080/02813432.2025.2490921

Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data

Autoren: Maksut Kulzhanov Alexander Wagner Abylkair Skakov et al.

Quelle: Central Asian Journal of Medical Hypotheses and Ethics, Vol 6, Iss 2, Pp 133-141 (2025)

Schlagwörter: machine learning, R723-726, Medical philosophy. Medical ethics, health insurance, healthcare analytics, data science, artificial intelligence, kazakhstan, predictive modeling

Zugangs-URL: https://doaj.org/article/8a5fba8964624021b7c8778cad08f485

Dynamic Healthcare Intelligence: Integrating AI Predictive Analytics with Kubernetes Scaling for Enhanced Patient Outcomes

Autoren: Shaik, Nawazpasha

Quelle: World Journal of Advanced Research and Reviews. 26:2534-2543

Schlagwörter: Human-AI Collaboration, Kubernetes Scaling, Medical Resource Optimization, Predictive Healthcare Analytics, Real-Time Clinical Decision Support

Multi-layer encrypted learning for distributed healthcare analytics

Autoren: Timothy Kuo Hui Yang

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Schlagwörter: Internet of medical things (IoMT), Data privacy, Fully homomorphic encryption (FHE), Federated learning, Healthcare analytics, Intensive care units (ICUs), Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/5e9682bb0d6e4220925e8ba9d01f5e1c

Optimization of Emergency Services at Hospital Beatriz Ângelo

Autoren: Falcato, Marta Maria Cavaco Martins, João Francisco Ribeiro da Silva RUN

Weitere Verfasser: Falcato, Marta Maria Cavaco Martins, João Francisco Ribeiro da Silva RUN

Schlagwörter: Emergency Department, Predictive Modelling, Hospital Operations, Resource Allocation, Healthcare Analytics, SDG 3 - Good health and well-being, Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação

Dateibeschreibung: application/pdf

Verfügbarkeit: http://hdl.handle.net/10362/190197

Transformative applications of Artificial Intelligence in infectious disease forecasting and public health decision support systems

Autoren: Omale, Lauretta Ekanem Ibiam, Victor Akachukwu Sidikat, Lasisi Wuraola et al.

Quelle: World Journal of Advanced Research and Reviews. 25:2250-2258

Schlagwörter: Artificial intelligence, Disease forecasting, Healthcare analytics, Decision support systems, Public health informatics, Predictive modeling

Strategic procurement practices in healthcare organizations and their impact on Medicaid and Medicare cost containment

Autoren: Balogun, Adeseun Kafayat Alaba, Helen Ayodimeji Adebayo, Kaosara Temitope et al.

Quelle: World Journal of Advanced Research and Reviews. 25:1863-1872

Schlagwörter: Cost Containment, Healthcare Analytics, Value-Based Procurement, Strategic Healthcare Procurement, Supply Chain Management, Digital Transformation

Improving Cardiovascular Disease Prediction With Deep Learning and Correlation-Aware SMOTE

Autoren: Maria Trigka Elias Dritsas

Quelle: IEEE Access, Vol 13, Pp 44590-44606 (2025)

Schlagwörter: Cardiovascular disease prediction, class imbalance, deep learning, healthcare analytics, Electrical engineering. Electronics. Nuclear engineering, enhanced SMOTE, TK1-9971

Zugangs-URL: https://doaj.org/article/b621fc2b81484f5c94054e349288aa8f

How accurately can supervised machine learning model predict a targeted psychiatric disorder?

Autoren: Jahrami, Haitham Pakpour, Amir H. Husain, Waqar et al.

Quelle: BMC Psychiatry. 24(1)

Schlagwörter: Artificial Intelligence, Disease Assessment, Healthcare Analytics, Hoarding disorders, Machine learning

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-66493
https://doi.org/10.1186/s12888-024-06152-w

Comprehensive survival analysis of breast cancer patients: a bayesian network approach

Autoren: Khaled Toffaha Mecit Can Emre Simsekler Aamna Al Shehhi et al.

Quelle: BMC Medical Informatics and Decision Making, Vol 25, Iss 1, Pp 1-21 (2025)

Schlagwörter: Breast cancer, Survival analysis, Machine learning, Bayesian belief network, Healthcare analytics, Computer applications to medicine. Medical informatics, R858-859.7

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1472-6947

Zugangs-URL: https://doaj.org/article/38156022545b4f53a912c430cfa216e5

Mamba-fusion for privacy-preserving disease prediction

Autoren: Muhammad Kashif Jabbar Huang Jianjun Ayesha Jabbar et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-20 (2025)

Schlagwörter: Privacy-preserving federated learning, Multi-modal data fusion, Hierarchical aggregation mechanism, Chronic disease prediction, Differential privacy in healthcare, Scalable healthcare analytics, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/c485cddf35a142c8921127cf28c9e765

Efficient Cardiovascular Disease Prognosis Through Compound Machine Learning Methods

Autoren: Puranam, Yuvaraj Katukoori, Shekhar Kumar, Chikati Aravind et al.

Schlagwörter: Machine Learning, Healthcare Analytics, Random Forest, Hybrid Algorithms, Heart Disease Prediction, Predictive Modeling, Gradient Boosting, Ensemble Learning

Predictive Modelling for Hospital Readmission Using Socioeconomic and Clinical Data

Autoren: Azeez Kunle, Akinbode Florence, Ifeanyichukwu Olinmah Onyeka, Kelvin Chima et al.

Quelle: Engineering and Technology Journal. 10

Schlagwörter: Hospital Readmission, Predictive Modeling, Socioeconomic Data, Clinical Data, Machine Learning, Healthcare Analytics, Social Determinants ofHealth, Electronic Health Records, Value-Based Care, Risk Stratification

Machine Learning in Healthcare

Autoren: Karam, Ahmed

Quelle: European Journal of Science, Innovation and Technology; Vol. 5 No. 4 (2025); 25-42

Schlagwörter: machine learning, medical imaging, healthcare analytics, artificial intelligence, predictive modeling

Dateibeschreibung: application/pdf

Zugangs-URL: https://ejsit-journal.com/index.php/ejsit/article/view/696

A Review of Machine Learning Techniques for Risk Evaluation in Healthcare and Insurance Systems

Autoren: Rathore, Dr. Prithviraj Singh

Schlagwörter: Healthcare Analytics, Machine Learning (ML), Insurance Fraud Detection, Patient Stratification, Predictive Modeling, Claims Management, Risk Assessment

Breaking Data Silos in Healthcare: A Novel Framework for Standardizing and Integrating NHS Medical Data for Advanced Analytics

Autoren: Thomas, Daniel

Schlagwörter: Healthcare Analytics, Data Standardization, Big data in Healthcare

Efficient Diabetes Prediction Using Random Forests and Minimal Health Indicators on the BRFSS Dataset

Autoren: Recep, Benzer

Schlagwörter: Healthcare Analytics, Random Forest, Diabetes Prediction, Feature Selection, BRFSS Dataset

Generative AI for Semantic Document Comparison in Medical Records: A Comprehensive Survey

Autoren: Sudha V.Salake Dr.S.P.Bangarashetti

Schlagwörter: Generative AI, Medical Records, Semantic Comparison, Electronic Health Records, Natural Language Processing, Healthcare Analytics, Large Language Models

A Systematic Survey of Artificial Intelligence in Disease Detection and Diagnosis

Autoren: Prachi Gaikwad Dr. Dheeraj Hebri Dr.M. B. Wagh

Schlagwörter: Natural language processing, medical imaging, machine learning, deep learning, artificial intelligence, illness detection, and healthcare analytics

Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector

Autoren: Utsav Pandey Sanjeet Singh

Quelle: International Journal of Mathematical, Engineering and Management Sciences, Vol 10, Iss 2, Pp 300-349 (2025)

Schlagwörter: healthcare efficiency, quality, dea, healthcare analytics, Technology, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://www.ijmems.in/cms/storage/app/public/uploads/volumes/17-IJMEMS-24-0599-10-2-300-349-2025.pdf; https://doaj.org/toc/2455-7749

Zugangs-URL: https://doaj.org/article/f623149f504e42729e4bc8998dd3a2c1