Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Sanparith Marukatat"'
Autor:
Roongruedee Chaiteerakij, Darlene Ariyaskul, Kittipat Kulkraisri, Terapap Apiparakoon, Sasima Sukcharoen, Oracha Chaichuen, Phaiboon Pensuwan, Thodsawit Tiyarattanachai, Rungsun Rerknimitr, Sanparith Marukatat
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract The effectiveness of ultrasonography (USG) in liver cancer screening is partly constrained by the operator’s expertise. We aimed to develop and evaluate an AI-assisted system for detecting and classifying focal liver lesions (FLLs) from US
Externí odkaz:
https://doaj.org/article/a2161e037cd547b78956e30522e7da6e
Autor:
Nanicha Siriwong, Thanikan Sukaram, Rossarin Tansawat, Terapap Apiparakoon, Thodsawit Tiyarattanachai, Sanparith Marukatat, Rungsun Rerknimitr, Roongruedee Chaiteerakij
Publikováno v:
Liver Research, Vol 6, Iss 3, Pp 191-197 (2022)
Objectives: The difficulties in the early detection consequent to the lack of sensitive biomarkers render patients with cholangiocarcinoma (CCA) to have poor outcomes. Recently, sensitive and specific volatile organic compounds (VOCs) were identified
Externí odkaz:
https://doaj.org/article/90e26b020123401b961a9604f69650f8
Autor:
Thodsawit Tiyarattanachai, Terapap Apiparakoon, Sanparith Marukatat, Sasima Sukcharoen, Sirinda Yimsawad, Oracha Chaichuen, Siwat Bhumiwat, Natthaporn Tanpowpong, Nutcha Pinjaroen, Rungsun Rerknimitr, Roongruedee Chaiteerakij
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Despite the wide availability of ultrasound machines for hepatocellular carcinoma surveillance, an inadequate number of expert radiologists performing ultrasounds in remote areas remains a primary barrier for surveillance. We demonstrated fe
Externí odkaz:
https://doaj.org/article/664c88e475cf49489a754d4714c53af4
Autor:
Thanikan Sukaram, Rossarin Tansawat, Terapap Apiparakoon, Thodsawit Tiyarattanachai, Sanparith Marukatat, Rungsun Rerknimitr, Roongruedee Chaiteerakij
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract Volatile organic compounds (VOCs) profile for diagnosis and monitoring therapeutic response of hepatocellular carcinoma (HCC) has not been well studied. We determined VOCs profile in exhaled breath of 97 HCC patients and 111 controls using g
Externí odkaz:
https://doaj.org/article/4d781fe5eb4b47c28c9f45b27a1060ff
Autor:
Thanikan Sukaram, Terapap Apiparakoon, Thodsawit Tiyarattanachai, Darlene Ariyaskul, Kittipat Kulkraisri, Sanparith Marukatat, Rungsun Rerknimitr, Roongruedee Chaiteerakij
Publikováno v:
Diagnostics, Vol 13, Iss 2, p 257 (2023)
Background: Volatile organic compound (VOC) profiles as biomarkers for hepatocellular carcinoma (HCC) are understudied. We aimed to identify VOCs from the exhaled breath for HCC diagnosis and compare the performance of VOCs to alpha-fetoprotein (AFP)
Externí odkaz:
https://doaj.org/article/2e35811f2267438aaade82b42bf9ae1d
Autor:
Thodsawit Tiyarattanachai, Terapap Apiparakoon, Sanparith Marukatat, Sasima Sukcharoen, Nopavut Geratikornsupuk, Nopporn Anukulkarnkusol, Parit Mekaroonkamol, Natthaporn Tanpowpong, Pamornmas Sarakul, Rungsun Rerknimitr, Roongruedee Chaiteerakij
Publikováno v:
PLoS ONE, Vol 16, Iss 6, p e0252882 (2021)
Artificial intelligence (AI) using a convolutional neural network (CNN) has demonstrated promising performance in radiological analysis. We aimed to develop and validate a CNN for the detection and diagnosis of focal liver lesions (FLLs) from ultraso
Externí odkaz:
https://doaj.org/article/2b659181f8be4df491eea6c38b6c6b02
Autor:
Nattanun Thatphithakkul, Boontee Kruatrachue, Chai Wutiwiwatchai, Sanparith Marukatat, Vataya Boonpiam
Publikováno v:
ASEAN Journal on Science and Technology for Development, Vol 24, Iss 4, Pp 339-352 (2017)
This paper proposes an efficient method of simulated-data adaptation for robust speech recognition. The method is applied to tree-structured piecewise linear transformation (PLT). The original PLT selects an acoustic model using tree-structured HMMs
Externí odkaz:
https://doaj.org/article/3ab89abf66b8405fa81433ba0736bb4e
Autor:
Sanparith Marukatat
Publikováno v:
Artificial Intelligence Review. 56:5445-5477
Principal Component Analysis (PCA) is one of the most widely used data analysis methods in machine learning and AI. This manuscript focuses on the mathematical foundation of classical PCA and its application to a small-sample-size scenario and a larg
Publikováno v:
2022 17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP).
Autor:
Sarin Watcharabutsarakham, Sanparith Marukatat, Kantip Kiratiratanapruk, Pitchayagan Temniranrat
Publikováno v:
2022 17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP).