AIMC Topic: Fever

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MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.

Journal of travel medicine
BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence...

A Deep Learning Framework for Image-Based Screening of Kawasaki Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Kawasaki disease (KD) is a leading cause of acquired heart disease in children and is characterized by the presence of a combination of five clinical signs assessed during the physical examination. Timely treatment of intravenous immunoglobin is need...

Scrub typhus: An under-reported and emerging threat - hospital based study from central and eastern Uttar Pradesh, India.

Journal of vector borne diseases
BACKGROUND & OBJECTIVES: Scrub typhus is a zoonotic rickettsial disease that is transmitted by the bite of the larval stage (chiggers) of trombiculid mites. The aim of this study was to determine the existence of scrub typhus in central and eastern U...

Machine Learning To Predict Serious Bacterial Infections in Young Febrile Infants.

Pediatrics
BACKGROUND: Recent decision rules for the management of febrile infants support the identification of infants at higher risk of serious bacterial infections (SBIs) without the performance of routine lumbar puncture. We derive and validate a model to ...

Prediction of fatal adverse prognosis in patients with fever-related diseases based on machine learning: A retrospective study.

Chinese medical journal
BACKGROUND: Fever is the most common chief complaint of emergency patients. Early identification of patients at an increasing risk of death may avert adverse outcomes. The aim of this study was to establish an early prediction model of fatal adverse ...

Classification of Infectious and Noninfectious Diseases Using Artificial Neural Networks from 24-Hour Continuous Tympanic Temperature Data of Patients with Undifferentiated Fever.

Critical reviews in biomedical engineering
Fever is one of the major clinical symptoms of undifferentiated fever cases. Early diagnosis of undifferentiated fever is a challenging task for the physician. The aim of this study was to classify infectious and noninfectious diseases from 24-hour c...