The Diagnosis of Dengue in Patients Presenting With Acute Febrile Illness Using Supervised Machine Learning and Impact of Seasonality.
Damien K. MingNguyen M. TuanBernard HernandezSorawat SangkaewNguyen L. VuongHo Q. ChanhNguyen V. V. ChauCameron P. SimmonsBridget WillsPantelis GeorgiouAlison H. HolmesSophie YacoubPublished in: Frontiers Digit. Health (2022)
Keyphrases
- supervised machine learning
- acute myeloid
- clinically relevant
- cardiovascular disease
- medical doctors
- critical care
- early diagnosis
- manually annotated
- spect images
- risk factors
- diagnostic tests
- medical practitioners
- medical diagnosis
- heart disease
- clinical diagnosis
- active learning
- ischemic stroke
- differential diagnosis
- health care providers
- chronic disease
- medical practice
- medical knowledge
- machine learning
- high risk
- early detection
- health care
- clinical data
- normal subjects
- supervised learning
- clinical trials
- medical data
- unsupervised learning
- ground truth
- domain knowledge
- high quality
- decision trees
- artificial intelligence