A Fluid-Structure Interaction Analysis of Blood Clot Motion in a Branch of Pulmonary Arteries

In silico analysis of embolism in cerebral arteries using fluid-structure interaction method

“…Equation (3) describes the stress in terms of viscoelastic constants, as outlined in Eqs. (1) and (2) [ 21 ]. …”

“…In another study by Ref. [ 21 ], the motion of clots inside a branch of pulmonary arteries, and the effect of their mechanical properties on their movement and the stress they experienced, was investigated. Another study revealed that employing 3D Monte Carlo simulations for embolic stroke enables predictions regarding the sizes and locations of lesions resulting from particular embolization patterns [ 22 ].…”

Exploring the Capabilities of a Lightweight CNN Model in Accurately Identifying Renal Abnormalities: Cysts, Stones, and Tumors, Using LIME and SHAP

“…Despite its limitations, such as non-standardized image acquisition [12]; the improper labeling of data collected; and regulatory barriers [13], deep-learning (DL) research has show a significant positive impact in radiology applications, such as reducing the workload of radiologists [14]; increasing medical access in developing countries and rural areas [15]; and improving diagnostic accuracy [16]. DL models have been applied for a wide range of concerns, such as COVID-19 [17], brain tumors [18], radiation therapy [19], blood clotting [20], heart diseases [21], liver cancer [22], fin-tech [23], intrusion detection [24], vibration signals [25], organic pollutant classification [26], agriculture [27], and steganography [28]. Recent research has shown that DL models can be used successfully for diagnosing kidney abnormalities [29][30][31][32][33].…”