Zobrazeno 1 - 10
of 101
pro vyhledávání: '"Nam Nhut Phan"'
Autor:
Untari Novia Wisesty, Ayu Purwarianti, Adi Pancoro, Amrita Chattopadhyay, Nam Nhut Phan, Eric Y. Chuang, Tati Rajab Mengko
Publikováno v:
IEEE Access, Vol 10, Pp 9004-9021 (2022)
The sequential labeling model is commonly used for time series or sequence data where each instance label is classified using previous instance label. In this work, a sequential labeling model is proposed as a new approach to detect the type and inde
Externí odkaz:
https://doaj.org/article/865a8681437e437b835ea38cb8413c9e
Autor:
Yen-Hung Wu, I-Jeng Yeh, Nam Nhut Phan, Meng-Chi Yen, Jui-Hsiang Hung, Chung-Chieh Chiao, Chien-Fu Chen, Zhengda Sun, Hui-Ping Hsu, Chih-Yang Wang, Ming-Derg Lai
Publikováno v:
Journal of Microbiology, Immunology and Infection, Vol 54, Iss 5, Pp 845-857 (2021)
Background: Pathogenic coronaviruses include Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2. These viruses have induced outbreaks worldwide, and there are currently no
Externí odkaz:
https://doaj.org/article/7e6444b82eac4c1286777a043bf79e7a
Autor:
Ming-Hung Shen, Chi-Cheng Huang, Yu-Tsung Chen, Yi-Jian Tsai, Fou-Ming Liou, Shih-Chang Chang, Nam Nhut Phan
Publikováno v:
Diagnostics, Vol 13, Iss 8, p 1473 (2023)
The present study aimed to develop an AI-based system for the detection and classification of polyps using colonoscopy images. A total of about 256,220 colonoscopy images from 5000 colorectal cancer patients were collected and processed. We used the
Externí odkaz:
https://doaj.org/article/66d84f2ac9e7426fa839abc08381728d
Autor:
Gangga Anuraga, Wan-Chun Tang, Nam Nhut Phan, Hoang Dang Khoa Ta, Yen-Hsi Liu, Yung-Fu Wu, Kuen-Haur Lee, Chih-Yang Wang
Publikováno v:
Current Issues in Molecular Biology, Vol 43, Iss 1, Pp 2-20 (2021)
Colorectal cancer (CRC) has the fourth-highest incidence of all cancer types, and its incidence has steadily increased in the last decade. The general transcription factor III (GTF3) family, comprising GTF3A, GTF3B, GTF3C1, and GTFC2, were stated to
Externí odkaz:
https://doaj.org/article/0c273cb987ea499d8cbe8521af96217d
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
We proposed a highly versatile two-step transfer learning pipeline for predicting the gene signature defining the intrinsic breast cancer subtypes using unannotated pathological images. Deciphering breast cancer molecular subtypes by deep learning ap
Externí odkaz:
https://doaj.org/article/5fd822eabb5f4ec8b5c3953244c24d43
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
PurposeThe present study aimed to assign a risk score for breast cancer recurrence based on pathological whole slide images (WSIs) using a deep learning model.MethodsA total of 233 WSIs from 138 breast cancer patients were assigned either a low-risk
Externí odkaz:
https://doaj.org/article/4942ebf6b8664ebeb7cecd72605ac372
Autor:
Chung-Chieh Chiao, Yen-Hsi Liu, Nam Nhut Phan, Nu Thuy An Ton, Hoang Dang Khoa Ta, Gangga Anuraga, Do Thi Minh Xuan, Fenny Fitriani, Elvira Mustikawati Putri Hermanto, Muhammad Athoillah, Vivin Andriani, Purity Sabila Ajiningrum, Yung-Fu Wu, Kuen-Haur Lee, Jian-Ying Chuang, Chih-Yang Wang, Tzu-Jen Kao
Publikováno v:
Diagnostics, Vol 11, Iss 12, p 2220 (2021)
The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer s
Externí odkaz:
https://doaj.org/article/61b4e1f02b4e422fb5b5ca79216944b7
Autor:
Gangga Anuraga, Wei-Jan Wang, Nam Nhut Phan, Nu Thuy An Ton, Hoang Dang Khoa Ta, Fidelia Berenice Prayugo, Do Thi Minh Xuan, Su-Chi Ku, Yung-Fu Wu, Vivin Andriani, Muhammad Athoillah, Kuen-Haur Lee, Chih-Yang Wang
Publikováno v:
Journal of Personalized Medicine, Vol 11, Iss 11, p 1089 (2021)
Breast cancer remains the most common malignant cancer in women, with a staggering incidence of two million cases annually worldwide; therefore, it is crucial to explore novel biomarkers to assess the diagnosis and prognosis of breast cancer patients
Externí odkaz:
https://doaj.org/article/1640d087d2354af3ac2a849d445bda8e
Autor:
Hoang Dang Khoa Ta, Wei-Jan Wang, Nam Nhut Phan, Nu Thuy An Ton, Gangga Anuraga, Su-Chi Ku, Yung-Fu Wu, Chih-Yang Wang, Kuen-Haur Lee
Publikováno v:
Cancers, Vol 13, Iss 19, p 4902 (2021)
In recent decades, breast cancer (BRCA) has become one of the most common diseases worldwide. Understanding crucial genes and their signaling pathways remain an enormous challenge in evaluating the prognosis and possible therapeutics. The “Like-Smi
Externí odkaz:
https://doaj.org/article/b557d952421348e98ff22626bbc8ca28
Autor:
Tak-Kee Choy, Chih-Yang Wang, Nam Nhut Phan, Hoang Dang Khoa Ta, Gangga Anuraga, Yen-Hsi Liu, Yung-Fu Wu, Kuen-Haur Lee, Jian-Ying Chuang, Tzu-Jen Kao
Publikováno v:
Diagnostics, Vol 11, Iss 7, p 1204 (2021)
Breast cancer is a heterogeneous disease involving complex interactions of biological processes; thus, it is important to develop therapeutic biomarkers for treatment. Members of the dipeptidyl peptidase (DPP) family are metalloproteases that specifi
Externí odkaz:
https://doaj.org/article/452a2186c703486eb2c8fc000925b762