Cargando…

Design and Development of an Intelligent System for Predicting 5-Year Survival in Gastric Cancer

BACKGROUND: Gastric cancer remains one of the leading causes of worldwide cancer-specific deaths. Accurately predicting the survival likelihood of gastric cancer patients can inform caregivers to boost patient prognostication and choose the best possible treatment path. This study intends to develop...

Descripción completa

Detalles Bibliográficos
Autores principales:	Afrash, Mohammad Reza, Shanbehzadeh, Mostafa, Kazemi-Arpanahi, Hadi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	SAGE Publications 2022
Materias:	Original Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9403452/ https://www.ncbi.nlm.nih.gov/pubmed/36035639 http://dx.doi.org/10.1177/11795549221116833

Ejemplares similares

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Predicting Risk of Mortality in COVID-19 Hospitalized Patients using Hybrid Machine Learning Algorithms
por: Afrash, Mohammad Reza, et al.
Publicado: (2022)

Developing the breast cancer risk prediction system using hybrid machine learning algorithms
por: Afrash, Mohammad R., et al.
Publicado: (2022)

Predicting hospital readmission risk in patients with COVID-19: A machine learning approach
por: Afrash, Mohammad Reza, et al.
Publicado: (2022)

Establishing machine learning models to predict the early risk of gastric cancer based on lifestyle factors
por: Afrash, Mohammad Reza, et al.
Publicado: (2023)

Optimizing prognostic factors of five-year survival in gastric cancer patients using feature selection techniques with machine learning algorithms: a comparative study
por: Afrash, Mohammad Reza, et al.
Publicado: (2023)

Design, development, and evaluation of a surveillance system for suicidal behaviors in Iran
por: Shafiee, Mohsen, et al.
Publicado: (2022)

Design of an artificial neural network to predict mortality among COVID-19 patients
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Design and development of a web‐based registry for Coronavirus (COVID‐19) disease
por: Kazemi-Arpanahi, Hadi, et al.
Publicado: (2020)

Developing a clinical decision support system based on the fuzzy logic and decision tree to predict colorectal cancer
por: Nopour, Raoof, et al.
Publicado: (2021)

Development of minimal basic data set to report COVID-19
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2020)

Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms
por: Yazdani, Azita, et al.
Publicado: (2023)

Developing an artificial neural network for detecting COVID-19 disease
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Development and evaluation of an electronic nursing documentation system
por: Shafiee, Mohsen, et al.
Publicado: (2022)

Predicting the Need for Intubation among COVID-19 Patients Using Machine Learning Algorithms: A Single-Center Study
por: Nopour, Raoof, et al.
Publicado: (2022)

Using logistic regression to develop a diagnostic model for COVID-19: A single-center study
por: Nopour, Raoof, et al.
Publicado: (2022)

Developing the minimum data set of the corrosive ingestion registry system in Iran
por: Mahmoudvand, Zahra, et al.
Publicado: (2022)

Prediction of successful aging using ensemble machine learning algorithms
por: Asghari Varzaneh, Zahra, et al.
Publicado: (2022)

Establishing a minimum data set for suicide and attempted suicide registry system in Iran
por: Shafiee, Mohsen, et al.
Publicado: (2022)

Predictive modeling for COVID-19 readmission risk using machine learning algorithms
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Comparing artificial neural network training algorithms to predict length of stay in hospitalized patients with COVID-19
por: Orooji, Azam, et al.
Publicado: (2022)

Coronavirus disease 2019 (COVID-19) surveillance system: Development of COVID-19 minimum data set and interoperable reporting framework
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2020)

Comparing machine learning algorithms for predicting COVID-19 mortality
por: Moulaei, Khadijeh, et al.
Publicado: (2022)

Performance evaluation of selected decision tree algorithms for COVID-19 diagnosis using routine clinical data
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2021)

Using decision tree algorithms for estimating ICU admission of COVID-19 patients
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Internet of Things (IoT) Adoption Model for Early Identification and Monitoring of COVID-19 Cases: A Systematic Review
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2022)

Data integration in cardiac electrophysiology ablation toward achieving proper interoperability in health information systems
por: Kazemi-Arpanahi, Hadi, et al.
Publicado: (2020)

Performance evaluation of selected machine learning algorithms for COVID-19 prediction using routine clinical data: With versus Without CT scan features
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2021)

Notifiable diseases interoperable framework toward improving Iran public health surveillance system: Lessons learned from COVID-19 pandemic
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2021)

Survey of the patients' perspectives and preferences in adopting telepharmacy versus in-person visits to the pharmacy: a feasibility study during the COVID-19 pandemic
por: Moulaei, Khadijeh, et al.
Publicado: (2022)

Performance analysis of data mining algorithms for diagnosing COVID-19
por: Nopour, Raoof, et al.
Publicado: (2021)

Factors influencing quality of life among the elderly: An approach using logistic regression
por: Ahmadi, Maryam, et al.
Publicado: (2023)

Systematic review on telemedicine platforms in lockdown periods: Lessons learned from the COVID-19 pandemic
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2021)

Design a Fuzzy Rule-based Expert System to Aid Earlier Diagnosis of Gastric Cancer
por: Safdari, Reza, et al.
Publicado: (2018)

Which are best for successful aging prediction? Bagging, boosting, or simple machine learning algorithms?
por: Mirzaeian, Razieh, et al.
Publicado: (2023)

Diagnosis and Treatment of Coagulopathy Caused by the New Coronavirus: A Systematic Review and Meta-Analysis Protocol
por: Abbasian, Sadegh, et al.
Publicado: (2023)

Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry
por: Shanbehzadeh, Mostafa, et al.
Publicado: (2020)

Association of chest CT severity score with mortality of COVID-19 patients: a systematic review and meta-analysis
por: Zakariaee, Seyed Salman, et al.
Publicado: (2022)

Design, implementation, and evaluation of a CPOE system in a cancer care setting: A case study on the gastric cancer patients
por: Afrash, Mohammad Reza, et al.
Publicado: (2023)

Predicting intubation risk among COVID-19 hospitalized patients using artificial neural networks
por: Nopour, Raoof, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_nmh0bpnhqeg156fld6q4kmsbb9