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Building and analyzing machine learning-based warfarin dose prediction models using scikit-learn
Sangzin Ahn 대한임상약리학회 2022 Translational and Clinical Pharmacology Vol.30 No.4
For personalized drug dosing, prediction models may be utilized to overcome the inter-individual variability. Multiple linear regression has been used as a conventional method to model the relationship between patient features and optimal drug dose. However, linear regression cannot capture non-linear relationships and may be adversely affected by non-normal distribution and collinearity of data. To overcome this hurdle, machine learning models have been extensively adapted in drug dose prediction. In this tutorial, random forest and neural network models will be trained in tandem with a multiple linear regression model on the International Warfarin Pharmacogenetics Consortium dataset using the scikit-learn python library. Subsequent model analyses including performance comparison, permutation feature importance computation and partial dependence plotting will be demonstrated. The basic methods of model training and analysis discussed in this article may be implemented in drug dose-related studies.
Mahmood, Usman,Ahn, Sangzin,Yang, Eun-Jeong,Choi, Moonseok,Kim, Hyunju,Regan, Philip,Cho, Kwangwook,Kim, Hye-Sun Elsevier 2018 PHARMACOLOGICAL RESEARCH Vol.128 No.-
<P><B>Abstract</B></P> <P>Mounting evidence suggests that the etiology of autism spectrum disorders (ASDs) is profoundly influenced by exposure to environmental factors, although the precise molecular and cellular links remain ill-defined. In this study, we examined how exposure to valproic acid (VPA) during pregnancy is associated with an increased incidence of ASD. A mouse model was established by injecting VPA at embryonic day 13, and its behavioral phenotypes including impaired social interaction, increased repetitive behaviors and decreased nociception were observed at postnatal days 21–42. VPA-treated mice showed dysregulation of synaptic structure in cortical neurons, including a reduced proportion of filopodium-type and stubby spines and increased proportions of thin and mushroom-type spines, along with a decreased spine head size. We also found that VPA-treatment led to decreased expression of phosphate and tensin homolog (PTEN) and increased levels of <I>p</I>-AKT protein in the hippocampus and cortex. Our data suggest that there is a correlation between VPA exposure and dysregulation of PTEN with ASD-like behavioral and neuroanatomical changes, and this may be a potential mechanism of VPA-induced ASD.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Transforming clinical trials: the emerging roles of large language models
Jong-Lyul Ghim,Sangzin Ahn 대한임상약리학회 2023 Translational and Clinical Pharmacology Vol.31 No.3
Clinical trials are essential for medical research, but they often face challenges in matching patients to trials and planning. Large language models (LLMs) offer a promising solution, signaling a transformative shift in the field of clinical trials. This review explores the multifaceted applications of LLMs within clinical trials, focusing on five main areas expected to be implemented in the near future: enhancing patient-trial matching, streamlining clinical trial planning, analyzing free text narratives for coding and classification, assisting in technical writing tasks, and providing cognizant consent via LLM-powered chatbots. While the application of LLMs is promising, it poses challenges such as accuracy validation and legal concerns. The convergence of LLMs with clinical trials has the potential to revolutionize the efficiency of clinical trials, paving the way for innovative methodologies and enhancing patient engagement. However, this development requires careful consideration and investment to overcome potential hurdles.
Park Ce Hwan,Kwon Jihyeon,Lee Jong Tae,Ahn Sangzin 대한의학회 2023 Journal of Korean medical science Vol.38 No.17
Background: Medical students are known to be subjected to immense stress under competitive curricula and have a high risk of depression, burnout, anxiety and sleep disorders. There is a global trend of switching from norm-referenced assessment (NRA) to criterion-referenced assessment (CRA), and these changes may have influenced the quality of life (QOL), sleep phase, sleep quality, stress, burnout, and depression of the medical students. We hypothesized that there is a significant difference of QOL between CRA and NRA and that sleep, stress, burnout, and depression are the main contributors. Methods: By administering an online survey regarding QOL and its contributors to Korean medical students, 365 responses from 10 medical schools were recorded. To clarify the complex relationship between the multiple factors in play, we applied nonlinear machine learning algorithms and utilized causal structure learning techniques on the survey data. Results: Students with CRA had lower scores in stress (68.16 ± 11.29, 76.03 ± 12.38, P < 0.001), burnout (48.09 ± 11.23, 55.93 ± 13.07, P < 0.001), depression (12.77 ± 9.82, 16.44 ± 11.27, P = 0.003) and higher scores in QOL (95.79 ± 16.20, 89.65 ± 16.28, P < 0.001) compared with students with NRA. Multiple linear regression, permutation importance of the random forest model and the causal structure model showed that depression, stress and burnout are the most influential factors of QOL of medical students. Conclusion: Medical students from schools that use CRA showed higher QOL scores, as well as lower burnout, stress and depression when compared with students from schools that use NRA. These results may be used as a basis for granting justification for the transition to CRA.
Kim, Hee Jin,Shin, Ki Young,Chang, Keun-A,Ahn, Sangzin,Choi, Hee Soon,Kim, Hye-Sun,Suh, Yoo-Hun The Korean Society of Pharmacology 2014 The Korean Journal of Physiology & Pharmacology Vol.18 No.1
Dehydroevodiamine HCl (DHED) has been reported to prevent memory impairment and neuronal cell loss in a rat model with cognitive disturbance. We investigated the effect of DHED on memory impairment and behavioral abnormality caused by stress. We demonstrated that DHED can improve stress-induced memory impairments and depression-like behaviors by using open-field test, Y-maze test and forced swimming test. DHED treatment significantly recovered the decreases in the levels of neural cell adhesion molecule (NCAM) proteins caused by stress and the decreases in cell viability. Our results suggested that DHED is a potential drug candidate for neuronal death, memory impairment and depression induced by stress.
Hee Jin Kim.*,Ki Young Shin.*,Keun-A Chang,Sangzin Ahn,Hee Soon Choi,Hye-Sun Kim,Yoo-Hun Suh 대한생리학회-대한약리학회 2014 The Korean Journal of Physiology & Pharmacology Vol.18 No.1
DehydroevodiamineㆍHCl (DHED) has been reported to prevent memory impairment and neuronal cell loss in a rat model with cognitive disturbance. We investigated the effect of DHED on memory impairment and behavioral abnormality caused by stress. We demonstrated that DHED can improve stress-induced memory impairments and depression-like behaviors by using open-field test, Y-maze test and forced swimming test. DHED treatment significantly recovered the decreases in the levels of neural cell adhesion molecule (NCAM) proteins caused by stress and the decreases in cell viability. Our results suggested that DHED is a potential drug candidate for neuronal death, memory impair-ment and depression induced by stress.