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Toxicological Sciences : an Official Journal of the Society of Toxicology
|
January 9, 2018
In Silico Prediction of Chemical-Induced Hepatocellular Hypertrophy Using Molecular Descriptors
Kaori Ambe, Kana Ishihara, Tatsuya Ochibe, et al.
Regulatory Toxicology and Pharmacology : RTP
|
April 17, 2026
ExSERA: The Explainable Machine Learning Model for Skin Sensitization Risk Assessment
Kaori Ambe, Kei Kinoshita, Juri Tokunaga, et al.
Clinical Kidney Journal
|
November 2, 2023
Epidemiology and predictors of hyponatremia in a contemporary cohort of patients with malignancy: a retrospective cohort study
Miho Murashima, Kaori Ambe, Yuka Aoki, et al.
Clinical and Translational Science
|
January 6, 2025
Prediction of Cisplatin-Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information
Kaori Ambe, Yuka Aoki, Miho Murashima, et al.
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Search research articles
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Showing results (11-20 of 14) with videos related to
Sort By:
Page
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You have reached the last page of results.
This site can display upto 14 results.
Toxicological Sciences : an Official Journal of the Society of Toxicology
|
January 9, 2018
In Silico Prediction of Chemical-Induced Hepatocellular Hypertrophy Using Molecular Descriptors
Kaori Ambe, Kana Ishihara, Tatsuya Ochibe, et al.
Regulatory Toxicology and Pharmacology : RTP
|
April 17, 2026
ExSERA: The Explainable Machine Learning Model for Skin Sensitization Risk Assessment
Kaori Ambe, Kei Kinoshita, Juri Tokunaga, et al.
Clinical Kidney Journal
|
November 2, 2023
Epidemiology and predictors of hyponatremia in a contemporary cohort of patients with malignancy: a retrospective cohort study
Miho Murashima, Kaori Ambe, Yuka Aoki, et al.
Clinical and Translational Science
|
January 6, 2025
Prediction of Cisplatin-Induced Acute Kidney Injury Using an Interpretable Machine Learning Model and Electronic Medical Record Information
Kaori Ambe, Yuka Aoki, Miho Murashima, et al.
Page
of 2