a |
Artificial Neural Network | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
b |
Big Data | Big Data and machine learning in medicine: the main problems |
Big Data Analytics | Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records |
breast cancer | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
c |
children | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
Clinical Decision Support System | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |
clinical informatics | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |
clinical text processing | Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records |
d |
data analysis | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis Big Data and machine learning in medicine: the main problems |
Data Mining | Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records |
deep learning | Big Data and machine learning in medicine: the main problems |
e |
experiment design problems | Big Data and machine learning in medicine: the main problems |
Expert rules | Information Support Features of the Medical Research Process Conduction in a Huge Net Laboratory |
expert systems | Information Support Features of the Medical Research Process Conduction in a Huge Net Laboratory |
exponential growth model | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
f |
Final Height | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
Formal Concept Analysis | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |
g |
Growth Hormone Deficiency | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
i |
information | How to make clinical data actionable: an example of radiology quality management and peer-review system |
interval graphs | Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records |
k |
knowledge discovery | Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records |
l |
Laboratory information system (LIS) | Information Support Features of the Medical Research Process Conduction in a Huge Net Laboratory |
Laboratory researches | Information Support Features of the Medical Research Process Conduction in a Huge Net Laboratory |
m |
mathematical model | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
measurements processing and analyses | Modeling Framework for Medical Data Semantic Transformations |
medical data | Big Data and machine learning in medicine: the main problems |
Medical information systems | Big Data and machine learning in medicine: the main problems |
medicine | Big Data and machine learning in medicine: the main problems |
metastases in lymph nodes | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
model driven approach for domain specific intelligent information system development | Modeling Framework for Medical Data Semantic Transformations |
modeling framework | Modeling Framework for Medical Data Semantic Transformations |
models semantic transformations | Modeling Framework for Medical Data Semantic Transformations |
Mortality | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
o |
Ontology | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |
p |
personalized medicine | Subgroup Discovery for Treatment Optimization |
prediction | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
primary metastases | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
Primary Tumor | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
r |
Radiological | How to make clinical data actionable: an example of radiology quality management and peer-review system |
Regression | Artificial neural networks for prediction of final height in children with growth hormone deficiency |
s |
Secondary metastases | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
service | How to make clinical data actionable: an example of radiology quality management and peer-review system |
software | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |
subgroup analysis | Subgroup Discovery for Treatment Optimization |
subgroup discovery | Subgroup Discovery for Treatment Optimization |
survival | Consolidated mathematical growth Model of Breast Cancer CoMBreC |
t |
text mining | New Reality in Clinical Informatics and Explanation-oriented Methods of Data Analysis |