AIMC Topic: Fever
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Clinical evaluation of the newly developed infectious disease/fever screening radar system using the neural network and fuzzy grouping method for travellers with suspected infectious diseases at Narita International Airport Clinic.
The Journal of infection
Sep 28, 2015
An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method.
The Journal of infection
Dec 23, 2014
OBJECTIVES: To classify higher-risk influenza patients within 10 s, we developed an infectious disease and fever screening radar system.
Augmentation of Infrared Microscopy of White Blood Cells and Medical Measures for Rapid and Accurate Diagnosis of Bacterial or Viral Infections in Febrile Pediatric Oncology Patients: An Expert System-Based Study.
Analytical chemistry
Jul 1, 2025
Infectious diseases, a major contributor to high mortality rates, often exhibit similar symptoms, despite variations in immune responses to bacterial or viral infections. Rapidly differentiating bacterial infections from viral infections in febrile p...
Self-Supervised Temperature Representation Learning for Fever Screening.
IEEE transactions on cybernetics
Jul 1, 2025
Utilizing thermal infrared facial imaging for fever screening in public spaces has become a common strategy to curb the spread of influenza viruses. However, it is difficult to capture larger number of faces with fever labels, which makes learning fa...
Natural Language Processing to Identify Infants Aged 90 Days and Younger With Fevers Prior to Presentation.
Hospital pediatrics
Jan 1, 2025
OBJECTIVE: Natural language processing (NLP) can enhance research studies for febrile infants by more comprehensive cohort identification. We aimed to refine and validate an NLP algorithm to identify and extract quantified temperature measurements fr...
MALrisk: a machine-learning-based tool to predict imported malaria in returned travellers with fever.
Journal of travel medicine
Dec 10, 2024
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
Jul 1, 2023
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
Jan 1, 2021
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
Sep 1, 2020
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
Mar 5, 2020
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 ...
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