A5061309381- Treatment of Major Depression
- Antimicrobial Resistance in Staphylococcus
- Blood Pressure and Hypertension Studies
- Traditional Chinese Medicine Studies
- Pharmaceutical studies and practices
- Computational Drug Discovery Methods
- Schizophrenia research and treatment
- Bacterial Identification and Susceptibility Testing
- Pharmaceutical Practices and Patient Outcomes
- Venous Thromboembolism Diagnosis and Management
- Robot Manipulation and Learning
- Biosimilars and Bioanalytical Methods
- Traffic Prediction and Management Techniques
- Organ Transplantation Techniques and Outcomes
- Traditional Chinese Medicine Analysis
- Mental Health Research Topics
- Hepatitis C virus research
- Robotic Mechanisms and Dynamics
- Renal Transplantation Outcomes and Treatments
- Pneumonia and Respiratory Infections
- Transplantation: Methods and Outcomes
- Bipolar Disorder and Treatment
- Lung Cancer Treatments and Mutations
- Soft Robotics and Applications
- Inflammatory Biomarkers in Disease Prognosis
Shanghai University of Traditional Chinese Medicine
2022-2024
Hangzhou First People's Hospital
2024
Zhejiang University
2022-2024
Sheng Jing Hospital
2022
Henan University
2021
North China Electric Power University
2014
Cedars-Sinai Medical Center
2014
China University of Petroleum, Beijing
2013
Dalhousie University
2009-2010
Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative dosing strategies have been developed for optimization; however, the utilization of individual factors and extensibility insufficient. We aimed to develop an optimal algorithm based on high-dimensional data using proposed variable engineering machine-learning methods.This study a process that automatically generates second-order interactions. performed...
This study aimed to establish an optimal model predict vancomycin trough concentrations by using machine learning.We enrolled 407 pediatric patients (age < 18 years) who received intravenously and underwent therapeutic drug monitoring from June 2013 April 2020 at Xinhua Hospital affiliated Shanghai Jiaotong University School of Medicine. The median (interquartile range) age weight the were 2 (0.63-5) years 12 (7.8-19) kg. Vancomycin considered as target variable, eight different algorithms...
Tacrolimus is a major immunosuppressor against post-transplant rejection in kidney transplant recipients. However, the narrow therapeutic index of tacrolimus and considerable variability among individuals are challenges for outcomes. The aim this study was to compare different machine learning deep algorithms establish individualized dose prediction models by using best performing algorithm. Therefore, 10 commonly used we compared, TabNet algorithm outperformed other with highest R 2...
Background: Sertraline is a commonly employed antidepressant in clinical practice. In order to control the plasma concentration of sertraline within therapeutic window achieve best effect and avoid adverse reactions, personalized model predict necessary. Aims: This study aimed establish medication for patients with depression receiving based on machine learning provide reference clinicians formulate drug regimens. Methods: A total 415 496 samples from December 2019 July 2022 at First...
The aim of this study was to apply machine learning methods deeply explore the risk factors associated with adverse drug events (ADEs) and predict occurrence ADEs in Chinese pediatric inpatients. Data 1,746 patients aged between 28 days 18 years (mean age = 3.84 years) were included from January 1, 2013, December 31, 2015, Children’s Hospital Chongqing Medical University. There 247 cases ADE occurrence, which most common drugs inducing antibacterials. Seven algorithms, including eXtreme...
Lapatinib is used for the treatment of metastatic HER2(+) breast cancer. We aim to establish a prediction model lapatinib dose using machine learning and deep techniques based on real-world study. There were 149 cancer patients enrolled from July 2016 June 2017 at Fudan University Shanghai Cancer Center. The sequential forward selection algorithm random forest was applied variable selection. Twelve algorithms compared in terms their predictive abilities (logistic regression, SVM, forest,...
Abstract Background Being one of the most widespread, pervasive, and troublesome illnesses in world, depression causes dysfunction various spheres individual social life. Regrettably, despite obtaining evidence-based antidepressant medication, up to 70% people are going continue experience symptoms. Quetiapine, as commonly prescribed antipsychotic medication worldwide, has been reported an effective augmentation strategy antidepressants. The right quetiapine dose personalized treatment...
<title>Abstract</title> <bold>Background </bold>Hypoglycemia is the main obstacle for achieving optimal glucose management in diabetic patients. Despite advances understanding risk factors, current prediction models hypoglycemia often rely on static variables and are not optimized real-time assessment hospitalized This study aims to develop validate a machine learning (ML)-based model inpatient hypoglycemia, integrating dynamic clinical data improve accuracy utility. <bold>Methods Findings...
<title>Abstract</title> The full text of this preprint has been withdrawn, as it was submitted in error. Therefore, the authors do not wish work to be cited a reference. Questions should directed corresponding author.
Tacrolimus is a widely used immunosuppressive drug in patients with autoimmune diseases. It has narrow therapeutic window, thus requiring monitoring (TDM) to guide the clinical regimen. This study included 193 cases of tacrolimus TDM data diseases at Southern Medical University Nanfang Hospital from June 7, 2018, December 31, 2020. The identified nine important variables for concentration using sequential forward selection, including height, daily dose, other immunosuppressants, low-density...
Abstract Dual antiplatelet therapy (DAPT) with clopidogrel plus aspirin within 48 h of acute minor strokes and transient ischemic attacks (TIAs) has been indicated to effectively reduce the rate recurrent strokes. However, efficacy shown be affected by cytochrome P450 2C19 (CYP2C19) polymorphisms. Patients carrying loss-of-function alleles (LoFAs) at a low risk recurrence (ESRS < 3) cannot benefit from all may have an increased bleeding risk. In order optimize for these patients avoid...
This study aimed to establish a prediction model of quetiapine concentration in patients with schizophrenia and depression, based on real-world data via machine learning techniques assist clinical regimen decisions.A total 650 cases therapeutic drug monitoring (TDM) from 483 at the First Hospital Hebei Medical University 1 November 2019 31 August 2022 were included study. Univariate analysis sequential forward selection (SFS) implemented screen important variables influencing TDM. After...
The prognostic role of hemoglobin-to-red blood cell distribution width ratio (HRR) in HBV-related decompensated cirrhosis (HBV-DeCi) has not been established. present study is aimed at determining the potential HRR as a predictive factor for prognosis HBV-DeCi patients.The included 177 patients. clinical outcome was death 30 days. Multivariate regression analysis and receiver operating characteristic curve were applied to assess value poor outcomes.A total 26 patients (14.7%) had died by...
The accuracy of current prediction tools for venous thromboembolism (VTE) events following hernia surgery remains insufficient individualized patient management strategies. To address this issue, we have developed a machine learning (ML)-based model to dynamically predict in-hospital VTE in Chinese patients after surgery.ML models the postoperative were trained on cohort 11 305 adult with from CHAT-1 trial, which included across 58 institutions China. In data processing, imputation was...
Risperidone is an efficacious second-generation antipsychotic (SGA) to treat a wide spectrum of psychiatric diseases, whereas its active moiety (risperidone and 9-hydroxyrisperidone) concentration without therapeutic reference range may increase the risk adverse drug reactions. We aimed establish prediction model risperidone in next monitoring (TDM) based on initial TDM information using machine learning methods. A total 983 patients treated with between May 2017 2018 Beijing Anding Hospital...
Valproic acid/sodium valproate (VPA) is a widely used anticonvulsant drug for maintenance treatment of bipolar disorders. In order to balance the efficacy and adverse events VPA treatment, an individualized dose regimen necessary. This study aimed establish medication model patients with disorder based on machine learning deep techniques. The sequential forward selection (SFS) algorithm was applied selecting feature subset, random forest interpolating missing values. Then, we compared nine...
Background Variability exists in sertraline pharmacokinetic parameters individuals, especially obvious adolescents. We aimed to establish an individualized dosing model of for adolescents with depression based on artificial intelligence (AI) techniques.
We develop a model for predicting quetiapine levels in patients with depression, using machine learning to support decisions on clinical regimens.Inpatients diagnosed depression at the First Hospital of Hebei Medical University from 1 November 2019, 31 August were enrolled. The ratio training cohort testing was fixed 80%:20% whole dataset. Univariate analysis executed all information screen important variables influencing TDM. prediction abilities nine and deep algorithms compared. created...
A study on 70 acute lymphoblastic leukemia (ALL) children (age ≤16 years) treated with high-dose methotrexate (HD-MTX) in Sichuan Provincial People's Hospital was conducted. The aim of the to establish a risk-scoring model predict HD-MTX-induced liver injury, considering gene polymorphisms' effects. Data screening performed through t-test, chi-square test, and ridge regression, six predictors were identified: age, MTRR_AA, MTRR_AG, SLCO1B1_11045879_CC, albumin_1 day before MTX...
Tectochrysin (TEC) is a natural flavonoid with anti-inflammatory, antioxidant, antitumor, and wound-healing activity. However, little known about the therapeutic effects of TEC on inflammatory bowel disease (IBD). This study investigated anti-inflammatory effect IBD. Mice dextran sulfate sodium (DSS)-induced chronic colitis served as an in vivo model Lipopolysaccharide (LPS)-stimulated J774A.1 macrophages mouse bone marrow-derived (BMDMs) vitro models inflammation. In vivo, 0.5% (w/w)...
<h3>Introduction</h3> High variability in vancomycin exposure neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and area-under-curve (AUC0-24) targets are important to optimize treatment. The objective was evaluate whether machine learning (ML) can be used clinical practice predict these treatment calculate optimal individual <h3>Methodology</h3> C0 values were retrieved from a large neonatal dataset. Individual estimates of AUC0-24...