Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Suwimon Wonglaksanapimon"'
Autor:
Pairash Saiviroonporn, Suwimon Wonglaksanapimon, Warasinee Chaisangmongkon, Isarun Chamveha, Pakorn Yodprom, Krittachat Butnian, Thanogchai Siriapisith, Trongtum Tongdee
Publikováno v:
BMC Medical Imaging, Vol 22, Iss 1, Pp 1-10 (2022)
Abstract Background Artificial intelligence, particularly the deep learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) measurement on chest X-ray (CXR) images. In everyday clinical use, however, this technology
Externí odkaz:
https://doaj.org/article/a6a92c269dce456986863ae07fed0864
Autor:
Kornchanok Vareesangthip, Banthita Thanapattaraborisuth, Kullanuch Chanchairujira, Suwimon Wonglaksanapimon, Thawee Chanchairujira
Publikováno v:
Siriraj Medical Journal, Vol 75, Iss 3 (2023)
Objective: To compare LUS with other volume assessment methods, and to verify the prognostic value of LUS in Thai chronic HD patients. Materials and Methods: We conducted a prospective cohort study in 36 chronic HD patients. Volume status before t
Externí odkaz:
https://doaj.org/article/bfc4e9b12ade40519da0a8e1ce29514c
Publikováno v:
Siriraj Medical Journal, Vol 73, Iss 9, Pp 594-602 (2021)
Objective: To compare CT findings between malignant pleural mesothelioma (MPM) and metastatic pleural disease (MPD). Materials and Methods: CT chest images of 157 cases of pathologically-proven malignant pleural disease (21 MPM, 136 MPD) were retrosp
Externí odkaz:
https://doaj.org/article/74fbdd5780f542c59dc84650cd6ca5d0
Autor:
Pairash Saiviroonporn, Kanchanaporn Rodbangyang, Trongtum Tongdee, Warasinee Chaisangmongkon, Pakorn Yodprom, Thanogchai Siriapisith, Suwimon Wonglaksanapimon, Phakphoom Thiravit
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-11 (2021)
Abstract Background Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for C
Externí odkaz:
https://doaj.org/article/43771ac3ffc84d769f5417e801d17ea3
Publikováno v:
Siriraj Medical Journal, Vol 71, Iss 5, Pp 385-391 (2019)
Objective: The purpose of this study was to investigate the association between CT findings of invasive pulmonary aspergillosis and neutrophils level. Methods: This retrospective study included the patients diagnosed with invasive pulmonary aspergill
Externí odkaz:
https://doaj.org/article/89fd2c5e702d4b7ea78787d38c74086b
Autor:
Siri-on Tritrakarn, M.D., Nidcharat Arlaipol, M.D., Jate Lumyongsatien, M.D., Suwimon Wonglaksanapimon, M.D.
Publikováno v:
Siriraj Medical Journal, Vol 70, Iss 1, Pp 53-59 (2018)
Objective: To evaluate the accuracy of NECT compared with CECT of PNS for the detection of complicated sinusitis. Methods: A retrospective review of 96 patients (mean age, 51.78; range 20-84 years), including 44 men and 52 women, with clinically su
Externí odkaz:
https://doaj.org/article/70a68da4f225424b8ec0f4cfbfd3619b
Publikováno v:
Siriraj Medical Journal, Vol 73, Iss 9 (2021)
Siriraj Medical Journal, Vol 73, Iss 9, Pp 594-602 (2021)
Siriraj Medical Journal, Vol 73, Iss 9, Pp 594-602 (2021)
Objective: To compare CT findings between malignant pleural mesothelioma (MPM) and metastatic pleuraldisease (MPD).Materials and Methods: CT chest images of 157 cases of pathologically-proven malignant pleural disease(21 MPM, 136 MPD) were retrospect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae1453ec6c8ef1f0087ccdc4881a0eb2
https://doi.org/10.33192/smj.2021.77
https://doi.org/10.33192/smj.2021.77
Autor:
Trongtum Tongdee, Warasinee Chaisangmongkon, Kanchanaporn Rodbangyang, Phakphoom Thiravit, Pakorn Yodprom, Thanogchai Siriapisith, Pairash Saiviroonporn, Suwimon Wonglaksanapimon
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-11 (2021)
BMC Medical Imaging
BMC Medical Imaging
Background Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::172db3337fafe745cca1246ea08a555d
https://doaj.org/article/43771ac3ffc84d769f5417e801d17ea3
https://doaj.org/article/43771ac3ffc84d769f5417e801d17ea3
Autor:
Pairash Saiviroonporn, Suwimon Wonglaksanapimon, Warasinee Chaisangmongkon, Isarun Chamveha, Pakorn Yodprom, Krittachat Butnian, Thanogchai Siriapisith, Trongtum Tongdee
Publikováno v:
BMC medical imaging. 22(1)
Background Artificial intelligence, particularly the deep learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) measurement on chest X-ray (CXR) images. In everyday clinical use, however, this technology is usuall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::233603a75d3e9ac209047c58f809bac0
https://pubmed.ncbi.nlm.nih.gov/35296262
https://pubmed.ncbi.nlm.nih.gov/35296262
Autor:
Kriengkrai, Iemsawatdikul, Suwimon, Wonglaksanapimon, Varalee, Mingkwansook, Wimonrat, Lornimitdee
Publikováno v:
Journal of the Medical Association of Thailand = Chotmaihet thangphaet. 96(3)
Most of the metastatic lung lesions are relatively high contrast in comparison to the lung background and easily detected in non-contrast enhancement chest computed tomography alone (NECCT). Pediatric patients may get benefit from its minimal radiati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8b648c25ba7efb6e7bebce9afeca71a1
https://pubmed.ncbi.nlm.nih.gov/23539938
https://pubmed.ncbi.nlm.nih.gov/23539938