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Manish Dhyani

Researcher at Lahey Hospital & Medical Center

Publications -  36
Citations -  1284

Manish Dhyani is an academic researcher from Lahey Hospital & Medical Center. The author has contributed to research in topics: Elastography & Fatty liver. The author has an hindex of 13, co-authored 36 publications receiving 859 citations. Previous affiliations of Manish Dhyani include Johns Hopkins University & Carney Hospital.

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Current status of imaging in nonalcoholic fatty liver disease

TL;DR: The aim of this article is to review the current status of imaging methods for NAFLD risk stratification and management, including their diagnostic accuracy, limitations, and practical applicability.
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Shear-wave elastography for the estimation of liver fibrosis in chronic liver disease: determining accuracy and ideal site for measurement.

TL;DR: SWE estimates of liver stiffness obtained from the right upper lobe showed the best correlation with liver fibrosis severity and can potentially be used as a noninvasive test to differentiate intermediate degrees of Liver fibrosis in patients with liver disease.
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Machine learning for medical ultrasound: status, methods, and future opportunities.

TL;DR: Leading machine learning approaches and research directions in US are reviewed, with an emphasis on recent ML advances, and an outlook on future opportunities for ML techniques to further improve clinical workflow and US-based disease diagnosis and characterization is presented.
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Principles of ultrasound elastography

TL;DR: The physical principles of ultrasoundElastography are discussed, differences between different ultrasound elastographic techniques are discusses, and the advantages and disadvantages of these techniques in clinical practice are reviewed.
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Shear-Wave Elastography for the Preoperative Risk Stratification of Follicular-patterned Lesions of the Thyroid: Diagnostic Accuracy and Optimal Measurement Plane.

TL;DR: Evaluating the diagnostic accuracy of shear-wave elastography for the diagnosis of malignancy in follicular lesions and to identify the optimal SWE measurement plane indicates that SWE may be a valuable tool in preoperative malignant risk assessment of follicular-patterned thyroid nodules.