Cargando…

Using natural language processing and machine learning to identify breast cancer local recurrence

BACKGROUND: Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local recurrences in breast cancer patients can reduce the time-consuming work of a...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zeng, Zexian, Espino, Sasa, Roy, Ankita, Li, Xiaoyu, Khan, Seema A., Clare, Susan E., Jiang, Xia, Neapolitan, Richard, Luo, Yuan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2018
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6309052/ https://www.ncbi.nlm.nih.gov/pubmed/30591037 http://dx.doi.org/10.1186/s12859-018-2466-x

Ejemplares similares

Preoperative magnetic resonance imaging use and oncologic outcomes in premenopausal breast cancer patients
por: Zeng, Zexian, et al.
Publicado: (2020)

Discovering causal interactions using Bayesian network scoring and information gain
por: Zeng, Zexian, et al.
Publicado: (2016)

Conjugated equine estrogen and medroxyprogesterone acetate are associated with decreased risk of breast cancer relative to bioidentical hormone therapy and controls
por: Zeng, Zexian, et al.
Publicado: (2018)

Artificial intelligence: with an introduction to machine learning
por: Neapolitan, Richard E, et al.
Publicado: (2018)

Deep learning for cancer type classification and driver gene identification
por: Zeng, Zexian, et al.
Publicado: (2021)

Recurrence Networks in Natural Languages
por: Baeza-Blancas, Edgar, et al.
Publicado: (2019)

A New Method for Predicting Patient Survivorship Using Efficient Bayesian Network Learning
por: Jiang, Xia, et al.
Publicado: (2014)

Natural language annotation for machine learning
por: Pustejovsky, J, et al.
Publicado: (2012)

Somatic genetic aberrations in benign breast disease and the risk of subsequent breast cancer
por: Zeng, Zexian, et al.
Publicado: (2020)

Identifying primary and recurrent cancers using a SAS-based natural language processing algorithm
por: Strauss, Justin A, et al.
Publicado: (2013)

Using Natural Language Processing and Machine Learning to Identify Opioids in Electronic Health Record Data
por: McDermott, Sean P, et al.
Publicado: (2023)

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning
por: Carrell, David S, et al.
Publicado: (2022)

Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke
por: Kim, Chulho, et al.
Publicado: (2019)

Estimating Nonfatal Gunshot Injury Locations With Natural Language Processing and Machine Learning Models
por: Parker, Susan T.
Publicado: (2020)

Applied natural language processing with Python: implementing machine learning and deep learning algorithms for natural language processing
por: Beysolow, Taweh
Publicado: (2018)

AmericasNLI: Machine translation and natural language inference systems for Indigenous languages of the Americas
por: Kann, Katharina, et al.
Publicado: (2022)

Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports
por: Ong, Charlene Jennifer, et al.
Publicado: (2020)

The Colloquial Faculty for Languages, Cerebral Localization, and the Nature of Genius
Publicado: (1887)

Statistical and machine learning methods for spatially resolved transcriptomics data analysis
por: Zeng, Zexian, et al.
Publicado: (2022)

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation
por: Zhao, Yiqing, et al.
Publicado: (2021)

Natural language processing with TensorFlow: teach language to machines using Python's deep learning library
por: Ganegedara, Thushan
Publicado: (2018)

Building chatbots with Python: using natural language processing and machine learning
por: Raj, Sumit
Publicado: (2019)

Machine learning with PySpark: with natural language processing and recommender systems
por: Singh, Pramod
Publicado: (2019)

Machine learning in medicine: a practical introduction to natural language processing
por: Harrison, Conrad J., et al.
Publicado: (2021)

Machine Learning and Natural Language Processing in Mental Health: Systematic Review
por: Le Glaz, Aziliz, et al.
Publicado: (2021)

Inferring Aberrant Signal Transduction Pathways in Ovarian Cancer from TCGA Data
por: Neapolitan, Richard, et al.
Publicado: (2014)

Prevalence of Financial Considerations Documented in Primary Care Encounters as Identified by Natural Language Processing Methods
por: Skaljic, Meliha, et al.
Publicado: (2019)

Probabilistic methods for financial and marketing informatics
por: Neapolitan, Richard E, et al.
Publicado: (2007)

Contemporary artificial intelligence
por: Neapolitan, Richard E, et al.
Publicado: (2013)

Mining Pure, Strict Epistatic Interactions from High-Dimensional Datasets: Ameliorating the Curse of Dimensionality
por: Jiang, Xia, et al.
Publicado: (2012)

Study of Integrated Heterogeneous Data Reveals Prognostic Power of Gene Expression for Breast Cancer Survival
por: Neapolitan, Richard E., et al.
Publicado: (2015)

Natural language processing and recurrent network models for identifying genomic mutation-associated cancer treatment change from patient progress notes
por: Guan, Meijian, et al.
Publicado: (2019)

Where humans meet machines: innovative solutions for knotty natural-language problems
por: Neustein, Amy, et al.
Publicado: (2013)

Natural language processing and machine learning to assist radiation oncology incident learning
por: Mathew, Felix, et al.
Publicado: (2021)

Application of machine learning and natural language processing for predicting stroke-associated pneumonia
por: Tsai, Hui-Chu, et al.
Publicado: (2022)

Building the European Social Innovation Database with Natural Language Processing and Machine Learning
por: Gök, Abdullah, et al.
Publicado: (2022)

Identifying Silver Linings During the Pandemic Through Natural Language Processing
por: Lossio-Ventura, Juan Antonio, et al.
Publicado: (2021)

Natural language processing to identify reasons for sex disparity in statin prescriptions
por: Witting, Celeste, et al.
Publicado: (2023)

Natural Language Processing of Learners’ Evaluations of Attendings to Identify Professionalism Lapses
por: Heath, Janae K., et al.
Publicado: (2023)

Automata, languages, and machines
por: Eilenberg, Samuel, et al.
Publicado: (1974)

Cannot write session to /tmp/vufind_sessions/sess_7fdk7c7qbhno2ci000nuj3fr2n