Early detection and classification of liver diseases in ultrasound images using hybrid machine learning techniques-Reference-Cited by-同舟云学术

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Early detection and classification of liver diseases in ultrasound images using hybrid machine learning techniques

Published:2022-10-12 Issue:27 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Adaguru Yogegowda Prasad¹^ORCID,Metan Jyoti²,Ananda Kumar Kurilinga Sannalingappa³,Prasad Kumbenahalli Hanumanthegowda Shiva⁴

Affiliation:

1. Department of Computer Science and Engineering SJB Institute of Technology Bengaluru Karnataka India

2. Department of Information Technology ATRIA Institute of Technology Bengaluru India

3. Software Engineer R and D Bengaluru Karnataka India

4. Department of Computer Science and Engineering, GITAM School of Technology GITAM University (Bangalore campus) Doddaballapura Karnataka India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.7341

Reference32 articles.

1. Acute liver failure

2. A New Approach to Evaluate Drug Treatment Response of Ovarian Cancer Patients Based on Deformable Image Registration

3. A New Method for Modeling Preoperative Diagnosis of Ovarian Tumors

4. High-Throughput Biomarker Segmentation on Ovarian Cancer Tissue Microarrays via Hierarchical Normalized Cuts

5. Feasibility of Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T1 and T2 Mapping in a PET/MR Setting

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