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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...

Significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
OBJECTIVES: This study aims to identify significant symptoms and nonsymptom-related factors for malaria diagnosis in endemic regions of Indonesia.

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning.

PloS one
BACKGROUND: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of sympto...

ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes.

Journal of biomedical informatics
OBJECTIVE: Identifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide A...

Derivation of a natural language processing algorithm to identify febrile infants.

Journal of hospital medicine
BACKGROUND: Diagnostic codes can retrospectively identify samples of febrile infants, but sensitivity is low, resulting in many febrile infants eluding detection. To ensure study samples are representative, an improved approach is needed.

Explainable deep learning algorithm for distinguishing incomplete Kawasaki disease by coronary artery lesions on echocardiographic imaging.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Incomplete Kawasaki disease (KD) has often been misdiagnosed due to a lack of the clinical manifestations of classic KD. However, it is associated with a markedly higher prevalence of coronary artery lesions. Identifying cor...

Explainable deep learning model to predict invasive bacterial infection in febrile young infants: A retrospective study.

International journal of medical informatics
BACKGROUND: Machine learning models have demonstrated superior performance in predicting invasive bacterial infection (IBI) in febrile infants compared to commonly used risk stratification criteria in recent studies. However, the black-box nature of ...

Review of Robot-Assisted HIFU Therapy.

Sensors (Basel, Switzerland)
This paper provides an overview of current robot-assisted high-intensity focused ultrasound (HIFU) systems for image-guided therapies. HIFU is a minimally invasive technique that relies on the thermo-mechanical effects of focused ultrasound waves to ...

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...