Publications by authors named "F Zouari"

Aims: Access to echocardiography is a significant barrier to heart failure (HF) care in many low- and middle-income countries. In this study, we hypothesized that an artificial intelligence (AI)-enhanced point-of-care ultrasound (POCUS) device could enable the detection of cardiac dysfunction by nurses in Tunisia.

Methods And Results: This CUMIN study was a prospective feasibility pilot assessing the diagnostic accuracy of home-based AI-POCUS for HF conducted by novice nurses compared with conventional clinic-based transthoracic echocardiography (TTE).

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Article Synopsis
  • Chronic kidney disease (CKD) is a growing health problem, and scientists want to find easier ways to detect it at home.
  • Researchers studied a new method called frequency-difference electrical impedance tomography (fdEIT) to check for CKD using measurements from patients' kidneys.
  • Their findings suggest that using this home-based method can help detect CKD early and reduce the strain on hospitals and doctors.
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This study demonstrates the feasibility of predicting NAFLD using multi-spectral electrical impedance tomography (EIT), group source separation, constant reference EIT and anthropometric measures. Vibration-controlled Transient Elastography (VCTE) Controlled Attenuated Parameter (CAP; n = 121) and magnetic resonance imaging-proton density fat fraction (MRI-PDFF; n = 34) achieved a sensitivity of 70.9% and specificity of 73.

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Recently, deep learning based methods have shown potential as alternative approaches for lung time difference electrical impedance tomography (tdEIT) reconstruction other than traditional regularized least square methods, that have inherent severe ill-posedness and low spatial resolution posing challenges for further interpretation. However, the validation of deep learning reconstruction quality is mainly focused on simulated data rather than in vivo human chest data, and on image quality rather than clinical indicator accuracy. In this study, a variational autoencoder is trained on high-resolution human chest simulations, and inference results on an EIT dataset collected from 22 healthy subjects performing various breathing paradigms are benchmarked with simultaneous spirometry measurements.

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Recent development of affordable, portable and self-administrable electrical impedance tomography (EIT) system demonstrated the feasibility of using standalone EIT and subject's anthropometrics to predict the gold standard spirometry indicators for lung-function assessment. Compared to spirometry, the system showed the advantage of providing spatial mapping of the spirometry indicators. Nevertheless, the previous study was limited to healthy subjects.

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