Shinichi Nakajima
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Explore the profile of Shinichi Nakajima including associated specialties, affiliations and a list of published articles.
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Articles
26
Citations
64
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Recent Articles
1.
Tsukamoto S, Kobayashi K, Toyoda M, Tone A, Kawanami D, Suzuki D, et al.
Diabetes Obes Metab
. 2024 May;
26(8):3248-3260.
PMID: 38764356
Aim: To conduct a post hoc subgroup analysis of patients with type 2 diabetes (T2D) from the RECAP study, who were treated with sodium-glucose cotransporter-2 (SGLT2) inhibitor and glucagon-like peptide...
2.
Muta Y, Kobayashi K, Toyoda M, Tone A, Suzuki D, Tsuriya D, et al.
Front Pharmacol
. 2024 Apr;
15:1358573.
PMID: 38601470
Accumulating evidence has demonstrated that both SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1Ra) have protective effects in patients with diabetic kidney disease. Combination therapy with SGLT2i and GLP1Ra is...
3.
Kobayashi K, Toyoda M, Tone A, Kawanami D, Suzuki D, Tsuriya D, et al.
Diab Vasc Dis Res
. 2023 Dec;
20(6):14791641231222837.
PMID: 38096503
Aims: Combination therapy with sodium-glucose cotransporter inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP1Ras) is now of interest in clinical practice. The present study evaluated the effects of the preceding drug...
4.
Tsukamoto S, Kobayashi K, Toyoda M, Hatori N, Kanaoka T, Wakui H, et al.
Hypertens Res
. 2023 Oct;
47(3):628-638.
PMID: 37848562
Sodium-glucose cotransporter 2 inhibitor (SGLT2-I) shows excellent antihypertensive effects in addition to its hypoglycemic effects. However, whether body mass index (BMI) affects the antihypertensive effect of SGLT2-I remains unknown. We...
5.
Kobayashi K, Toyoda M, Hatori N, Tsukamoto S, Kimura M, Sakai H, et al.
Cardiovasc Endocrinol Metab
. 2023 Oct;
12(4):e0292.
PMID: 37779602
Aims: This study aimed to clarify the renal influence of glucagon-like peptide 1 receptor agonists (GLP1Ras) with or without sodium-glucose co-transporter 2 inhibitors (SGLT2is) on Japanese patients with type 2...
6.
Srinivasan V, Muller K, Samek W, Nakajima S
IEEE Trans Neural Netw Learn Syst
. 2022 Feb;
34(10):7675-7688.
PMID: 35133968
Domain translation is the task of finding correspondence between two domains. Several deep neural network (DNN) models, e.g., CycleGAN and cross-lingual language models, have shown remarkable successes on this task...
7.
Kobayashi K, Toyoda M, Hatori N, Sakai H, Furuki T, Chin K, et al.
Diabetes Res Clin Pract
. 2022 Feb;
185:109231.
PMID: 35131376
Aims: This study aimed to clarify the differences in how sodium glucose co-transporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1Ra) influence kidney function in Japanese patients with...
8.
Schnake T, Eberle O, Lederer J, Nakajima S, Schutt K, Muller K, et al.
IEEE Trans Pattern Anal Mach Intell
. 2021 Sep;
44(11):7581-7596.
PMID: 34559639
Graph Neural Networks (GNNs) are a popular approach for predicting graph structured data. As GNNs tightly entangle the input graph into the neural network structure, common explainable AI approaches are...
9.
Horiguchi Y, Uemura K, Aoyama N, Nakajima S, Asai T, Motohashi S, et al.
Ren Replace Ther
. 2021 Sep;
7(1):48.
PMID: 34513029
Background: Whether progressive mild to moderate aortic stenosis in hemodialysis patients influences their prognosis has not been elucidated. This prospective cohort study explored whether progressive aortic stenosis predicted the rate...
10.
Nicoli K, Anders C, Funcke L, Hartung T, Jansen K, Kessel P, et al.
Phys Rev Lett
. 2021 Feb;
126(3):032001.
PMID: 33543982
In this Letter, we demonstrate that applying deep generative machine learning models for lattice field theory is a promising route for solving problems where Markov chain Monte Carlo (MCMC) methods...