Tsukiyama S - Search Results

1

Cost-effectiveness of aprepitant in Japanese patients treated with cisplatin-containing highly emetogenic chemotherapy.

Tsukiyama I, Hasegawa S, Ikeda Y, Takeuchi M, Tsukiyama S, Kurose Y, Ejiri M, Sakuma M, Saito H, Arakawa I, Inoue T, Yamaguchi E, Kubo A. Tsukiyama I, et al. Among authors: tsukiyama s. Cancer Sci. 2018 Sep;109(9):2881-2888. doi: 10.1111/cas.13736. Epub 2018 Aug 3. Cancer Sci. 2018. PMID: 29999572 Free PMC article. Clinical Trial.

2

Cost-utility analysis of aprepitant for patients who truly need it in Japan.

Tsukiyama I, Ando M, Tsukiyama S, Takeuchi M, Ejiri M, Kurose Y, Saito H, Arakawa I, Inoue T, Yamaguchi E, Kubo A. Tsukiyama I, et al. Among authors: tsukiyama s. Support Care Cancer. 2019 Oct;27(10):3749-3758. doi: 10.1007/s00520-019-04672-w. Epub 2019 Feb 1. Support Care Cancer. 2019. PMID: 30710243

3

Factors associated with early discontinuation of anamorelin in patients with cancer-associated cachexia.

Tsukiyama I, Iwata T, Takeuchi T, Kato RI, Sakuma M, Tsukiyama S, Kato M, Ikeda Y, Ohashi W, Kubo A, Mori N. Tsukiyama I, et al. Among authors: tsukiyama s. Support Care Cancer. 2023 Oct 10;31(12):621. doi: 10.1007/s00520-023-08097-4. Support Care Cancer. 2023. PMID: 37815652 Free PMC article.

4

PredIL13: Stacking a variety of machine and deep learning methods with ESM-2 language model for identifying IL13-inducing peptides.

Kurata H, Harun-Or-Roshid M, Tsukiyama S, Maeda K. Kurata H, et al. Among authors: tsukiyama s. PLoS One. 2024 Aug 22;19(8):e0309078. doi: 10.1371/journal.pone.0309078. eCollection 2024. PLoS One. 2024. PMID: 39172871 Free PMC article.

5

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.

Kurata H, Harun-Or-Roshid M, Mehedi Hasan M, Tsukiyama S, Maeda K, Manavalan B. Kurata H, et al. Among authors: tsukiyama s. Methods. 2024 Jul;227:37-47. doi: 10.1016/j.ymeth.2024.05.004. Epub 2024 May 8. Methods. 2024. PMID: 38729455

6

CNN6mA: Interpretable neural network model based on position-specific CNN and cross-interactive network for 6mA site prediction.

Tsukiyama S, Hasan MM, Kurata H. Tsukiyama S, et al. Comput Struct Biotechnol J. 2022 Dec 28;21:644-654. doi: 10.1016/j.csbj.2022.12.043. eCollection 2023. Comput Struct Biotechnol J. 2022. PMID: 36659917 Free PMC article.

7

A HANC Risk Stratification Score for Antiplatelet Therapy Optimization with Low-Dose Prasugrel in Taiwanese Acute Coronary Syndrome Patients from the Switch Study.

Lee WL, Wang YC, Su CS, Lee HF, Tung YC, Liu PY, Su CH, Kuo FY, Lin WS, Chu PH, Lu TM, Lo PH, Tsukiyama S, Yang WC, Cheng LC, Yin WH, Lin YH. Lee WL, et al. Among authors: tsukiyama s. Acta Cardiol Sin. 2022 Nov;38(6):751-764. doi: 10.6515/ACS.202211_38(6).20220702A. Acta Cardiol Sin. 2022. PMID: 36440250 Free PMC article.

8

ICAN: Interpretable cross-attention network for identifying drug and target protein interactions.

Kurata H, Tsukiyama S. Kurata H, et al. Among authors: tsukiyama s. PLoS One. 2022 Oct 24;17(10):e0276609. doi: 10.1371/journal.pone.0276609. eCollection 2022. PLoS One. 2022. PMID: 36279284 Free PMC article.

9

Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention-based neural networks.

Tsukiyama S, Kurata H. Tsukiyama S, et al. Comput Struct Biotechnol J. 2022;20:5564-5573. doi: 10.1016/j.csbj.2022.10.012. Epub 2022 Oct 8. Comput Struct Biotechnol J. 2022. PMID: 36249566 Free PMC article.

10

iACVP: markedly enhanced identification of anti-coronavirus peptides using a dataset-specific word2vec model.

Kurata H, Tsukiyama S, Manavalan B. Kurata H, et al. Among authors: tsukiyama s. Brief Bioinform. 2022 Jul 18;23(4):bbac265. doi: 10.1093/bib/bbac265. Brief Bioinform. 2022. PMID: 35772910

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