Deep learning-based evaluation of the severity of mitral regurgitation in canine myxomatous mitral valve disease patients using digital stethoscope recordings.
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| Title: | Deep learning-based evaluation of the severity of mitral regurgitation in canine myxomatous mitral valve disease patients using digital stethoscope recordings. |
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| Authors: | Lee SY; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Lee S; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Kim SH; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Chang H; Smartsound Corporation, Seoul, Korea., Cho WY; Smartsound Corporation, Seoul, Korea., Ryu MO; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Choi J; Department of Veterinary Medical Imaging, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Yoon HY; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea., Seo KW; Department of Veterinary Clinical Science, Laboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Seoul National University, Seoul, 08826, Republic of Korea. kwseo@snu.ac.kr. |
| Source: | BMC veterinary research [BMC Vet Res] 2025 May 08; Vol. 21 (1), pp. 326. Date of Electronic Publication: 2025 May 08. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 101249759 Publication Model: Electronic Cited Medium: Internet ISSN: 1746-6148 (Electronic) Linking ISSN: 17466148 NLM ISO Abbreviation: BMC Vet Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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