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Alle Papers – Machine Learning im Gesundheitswesen

106.245 Papers insgesamt · Seite 6 von 400

126.

On evaluation metrics for medical applications of artificial intelligence

2022·815 Zit.·Scientific ReportsOA
127.

Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review

2018·812 Zit.·Journal of the American Medical Informatics AssociationOA
128.

Next-generation phenotyping of electronic health records

2012·811 Zit.·Journal of the American Medical Informatics AssociationOA
129.

Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction

2021·805 Zit.·npj Digital MedicineOA
130.

A large language model for electronic health records

2022·804 Zit.·npj Digital MedicineOA
131.

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU

2017·803 Zit.·Critical Care Medicine
132.

Machine Learning for Precision Psychiatry: Opportunities and Challenges

2017·793 Zit.·Biological Psychiatry Cognitive Neuroscience and Neuroimaging
133.

SVM-RFE: selection and visualization of the most relevant features through non-linear kernels

2018·790 Zit.·BMC BioinformaticsOA
134.

Supervised Machine Learning: A Brief Primer

2020·787 Zit.·Behavior TherapyOA
135.

Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

2014·784 Zit.·BMC Medical Research MethodologyOA
136.

An Introduction to Machine Learning

2020·783 Zit.·Clinical Pharmacology & TherapeuticsOA
137.

The ‘Digital Twin’ to enable the vision of precision cardiology

2020·780 Zit.·European Heart JournalOA
138.

Automatic Linkage of Vital Records

1959·778 Zit.·Science
139.

Electronic Health Records: Then, Now, and in the Future

2016·776 Zit.·Yearbook of Medical InformaticsOA
140.

2020 International Joint Conference on Neural Networks (IJCNN)

2020·774 Zit.
141.

Artificial Intelligence in Medical Practice: The Question to the Answer?

2017·770 Zit.·The American Journal of Medicine
142.

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

2015·764 Zit.·The Annals of Applied StatisticsOA
143.

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines

2020·764 Zit.·npj Digital MedicineOA
144.

XGBoost Model for Chronic Kidney Disease Diagnosis

2019·760 Zit.·IEEE/ACM Transactions on Computational Biology and Bioinformatics
145.

Addressing bias in big data and AI for health care: A call for open science

2021·759 Zit.·PatternsOA
146.

A computerized psychiatric diagnostic system and case nomenclature for elderly subjects: GMS and AGECAT

1986·757 Zit.·Psychological Medicine
147.

The ethics of artificial intelligence

2014·747 Zit.·Cambridge University Press eBooks
148.

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies

2020·734 Zit.·Journal of Biomedical InformaticsOA
149.

Sample size for binary logistic prediction models: Beyond events per variable criteria

2018·733 Zit.·Statistical Methods in Medical ResearchOA
150.

Improved Recurrent Neural Networks for Session-based Recommendations

2016·730 Zit.