Cargando…

Efficient analysis of COVID-19 clinical data using machine learning models

Because of the rapid spread of COVID-19 to almost every part of the globe, huge volumes of data and case studies have been made available, providing researchers with a unique opportunity to find trends and make discoveries like never before by leveraging such big data. This data is of many different...

Descripción completa

Detalles Bibliográficos
Autores principales:	Ali, Sarwan, Zhou, Yijing, Patterson, Murray
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Berlin Heidelberg 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9066140/ https://www.ncbi.nlm.nih.gov/pubmed/35507111 http://dx.doi.org/10.1007/s11517-022-02570-8

Ejemplares similares

Benchmarking machine learning robustness in Covid-19 genome sequence classification
por: Ali, Sarwan, et al.
Publicado: (2023)

PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences
por: Ali, Sarwan, et al.
Publicado: (2022)

Assessing the Resilience of Machine Learning Classification Algorithms on SARS-CoV-2 Genome Sequences Generated with Long-Read Specific Errors
por: Sahoo, Bikram, et al.
Publicado: (2023)

Exploring the Potential of GANs in Biological Sequence Analysis
por: Murad, Taslim, et al.
Publicado: (2023)

Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models
por: Morís, Daniel I., et al.
Publicado: (2023)

Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections
por: Sedik, Ahmed, et al.
Publicado: (2020)

Efficient clinical data analysis for prediction of coal workers' pneumoconiosis using machine learning algorithms
por: Dong, Hantian, et al.
Publicado: (2023)

Machine learning of COVID-19 clinical data identifies population structures with therapeutic potential
por: Greenwood, David, et al.
Publicado: (2022)

An efficient mixture of deep and machine learning models for COVID-19 diagnosis in chest X-ray images
por: Wang, Dingding, et al.
Publicado: (2020)

Machine learning with multimodal data for COVID-19
por: Chen, Weijie, et al.
Publicado: (2023)

Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis
por: Li, Wei Tse, et al.
Publicado: (2020)

Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
por: Chang, Victor, et al.
Publicado: (2022)

Hands-on data science and Python machine learning: perform data mining and machine learning efficiently using Python and Spark
por: Kane, Frank
Publicado: (2017)

Machine learning based approaches for detecting COVID-19 using clinical text data
por: Khanday, Akib Mohi Ud Din, et al.
Publicado: (2020)

Machine Learning Approach to Predicting COVID-19 Disease Severity Based on Clinical Blood Test Data: Statistical Analysis and Model Development
por: Aktar, Sakifa, et al.
Publicado: (2021)

A machine learning analysis of COVID-19 mental health data
por: Rezapour, Mostafa, et al.
Publicado: (2022)

Efficient Data-Driven Machine Learning Models for Cardiovascular Diseases Risk Prediction
por: Dritsas, Elias, et al.
Publicado: (2023)

Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data
por: Yazdani, Azita, et al.
Publicado: (2022)

Data and Power Efficient Intelligence with Neuromorphic Learning Machines
por: Neftci, Emre O.
Publicado: (2018)

Reformulating Reactivity Design for Data-Efficient Machine Learning
por: Lewis-Atwell, Toby, et al.
Publicado: (2023)

Efficient machine learning model for predicting drug-target interactions with case study for Covid-19
por: El-Behery, Heba, et al.
Publicado: (2021)

Machine-Learning Approaches in COVID-19 Survival Analysis and Discharge-Time Likelihood Prediction Using Clinical Data
por: Nemati, Mohammadreza, et al.
Publicado: (2020)

Predicting RPC eﬃciency using machine learning and deep learning models
por: Michelevicius, Mikas
Publicado: (2021)

CLINICAL CHARACTERISTICS AND OUTCOMES OF PATIENTS WITH COVID-19 IN A COMMUNITY HOSPITAL IN MICHIGAN
por: Tusha, Jurgena, et al.
Publicado: (2020)

Accuracy of Machine Learning Models to Predict Mortality in COVID-19 Infection Using the Clinical and Laboratory Data at the Time of Admission
por: Tabatabaie, Mohsen, et al.
Publicado: (2021)

Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques
por: Nadakinamani, Rajkumar Gangappa, et al.
Publicado: (2022)

A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data
por: Chieregato, Matteo, et al.
Publicado: (2022)

Predicting prognosis in COVID-19 patients using machine learning and readily available clinical data
por: Campbell, Thomas W., et al.
Publicado: (2021)

Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients
por: Cowley, Hannah Paris, et al.
Publicado: (2023)

Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation
por: Domínguez-Olmedo, Juan L, et al.
Publicado: (2021)

An Overview of Supervised Machine Learning Methods and Data Analysis for COVID-19 Detection
por: Tchagna Kouanou, Aurelle, et al.
Publicado: (2021)

Sentiment analysis of COVID-19 social media data through machine learning
por: Dangi, Dharmendra, et al.
Publicado: (2022)

Efficient Prediction of Missed Clinical Appointment Using Machine Learning
por: Qureshi, Zeeshan, et al.
Publicado: (2021)

Efficient Automated Disease Diagnosis Using Machine Learning Models
por: Kumar, Naresh, et al.
Publicado: (2021)

Data-efficient machine learning for molecular crystal structure prediction
por: Wengert, Simon, et al.
Publicado: (2021)

Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient
por: Agrawal, Tanay
Publicado: (2020)

Robust and efficient COVID-19 detection techniques: A machine learning approach
por: Hasan, Md. Mahadi, et al.
Publicado: (2022)

Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach
por: Li, Mengyuan, et al.
Publicado: (2021)

Machine Learning Assisted Prediction of Prognostic Biomarkers Associated With COVID-19, Using Clinical and Proteomics Data
por: Sardar, Rahila, et al.
Publicado: (2021)

Age-Stratified Analysis of COVID-19 Outcome Using Machine Learning Predictive Models
por: Domínguez-Olmedo, Juan L., et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_q8p1d9aklebfuopn1vmtggrrb0