Herbal medicine for inflammatory bowel diseases: development of pattern identification algorithms by retrospective analysis of case series data

Won, Jiyoon; Lee, Byung Hee; Jung, Won-Mo; Chae, Younbyoung; Lee, Hyangsook

doi:10.1016/j.eujim.2020.101114

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…Because the studies of Ung et al (2007a), Ung et al (2007b), Chen et al (2019), Yao et al (2019), andJiang et al (2016) are based on computer simulation using the established electronic database, the specific names of herbs or herbal prescriptions are not mentioned in Table 3. The case of Won et al (2020) is not summarized in Table 3 as the study focused on finding the pattern of herbal medicine.…”

Section: Results Using Artificial Intelligence In Herbal Medicinementioning

confidence: 99%

The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review

Chu¹,

Moon

Park

et al. 2022

Front. Pharmacol.

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Background: The development of artificial intelligence (AI) in the medical field has been growing rapidly. As AI models have been introduced in complementary and alternative medicine (CAM), a systematized review must be performed to understand its current status.Objective: To categorize and seek the current usage of AI in CAM.Method: A systematic scoping review was conducted based on the method proposed by the Joanna Briggs Institute. The three databases, PubMed, Embase, and Cochrane Library, were used to find studies regarding AI and CAM. Only English studies from 2000 were included. Studies without mentioning either AI techniques or CAM modalities were excluded along with the non-peer-reviewed studies. A broad-range search strategy was applied to locate all relevant studies.Results: A total of 32 studies were identified, and three main categories were revealed: 1) acupuncture treatment, 2) tongue and lip diagnoses, and 3) herbal medicine. Other CAM modalities were music therapy, meditation, pulse diagnosis, and TCM syndromes. The majority of the studies utilized AI models to predict certain patterns and find reliable computerized models to assist physicians.Conclusion: Although the results from this review have shown the potential use of AI models in CAM, future research ought to focus on verifying and validating the models by performing a large-scale clinical trial to better promote AI in CAM in the era of digital health.

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Section: Results Using Artificial Intelligence In Herbal Medicinementioning

confidence: 99%

The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review

Chu¹,

Moon

Park

et al. 2022

Front. Pharmacol.

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“…The prediction models for short-term (by LR or rbf-SVM) and long-term (by rbf-SVM and DT) remission showed good performance in our study. In IBD research, LR, SVM, and DT have been widely used to predict disease progression, course, risk factors, and treatment outcomes [ 35 , 36 , 37 , 38 , 39 , 40 ]. LR is a statistical model in which the probability of the outcome variable (dependent variables, Y) is predicted by the sigmoid function as a linear combination of potential predictor variables (independent variables, X) [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Clinical Remission with Adalimumab Therapy in Patients with Ulcerative Colitis by Fourier Transform–Infrared Spectroscopy Coupled with Machine Learning Algorithms

Kim,

Shin,

Saeed

et al. 2023

Metabolites

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We aimed to develop prediction models for clinical remission associated with adalimumab treatment in patients with ulcerative colitis (UC) using Fourier transform–infrared (FT–IR) spectroscopy coupled with machine learning (ML) algorithms. This prospective, observational, multicenter study enrolled 62 UC patients and 30 healthy controls. The patients were treated with adalimumab for 56 weeks, and clinical remission was evaluated using the Mayo score. Baseline fecal samples were collected and analyzed using FT–IR spectroscopy. Various data preprocessing methods were applied, and prediction models were established by 10-fold cross-validation using various ML methods. Orthogonal partial least squares–discriminant analysis (OPLS–DA) showed a clear separation of healthy controls and UC patients, applying area normalization and Pareto scaling. OPLS–DA models predicting short- and long-term remission (8 and 56 weeks) yielded area-under-the-curve values of 0.76 and 0.75, respectively. Logistic regression and a nonlinear support vector machine were selected as the best prediction models for short- and long-term remission, respectively (accuracy of 0.99). In external validation, prediction models for short-term (logistic regression) and long-term (decision tree) remission performed well, with accuracy values of 0.73 and 0.82, respectively. This was the first study to develop prediction models for clinical remission associated with adalimumab treatment in UC patients by fecal analysis using FT–IR spectroscopy coupled with ML algorithms. Logistic regression, nonlinear support vector machines, and decision tree were suggested as the optimal prediction models for remission, and these were noninvasive, simple, inexpensive, and fast analyses that could be applied to personalized treatments.

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“…Real-time PCR reactions were conducted using the Quantitect SYBR Green PCR kit, and primer specificity was confirmed by NCBI blast. Expression levels of target genes were normalized to GAPDH, and fold changes were calculated using the ddCT method [32][33][34][35].…”

Section: Analysis Of Gene Expression By Quantitative Real-time Pcr (Q...mentioning

confidence: 99%

Pharmacological Profiling and Therapeutic Evaluation of Herbal Plants in Inflammatory Bowel Disease Management

Naik,

Gupta

2023

JRTDD

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The objective of this research is to evaluate the effectiveness of combination therapy involving Trimetazidine with beta blockers, such as Metoprolol, in managing anginal episodes, given the limitations of traditional hemodynamic agents in treating all individuals with anginal problems. While medications like nitrates, beta-adrenergic antagonists, and calcium channel blockers are commonly used to reduce myocardial oxygen demand and alleviate cardiac strain, they often produce undesirable hemodynamic effects such as changes in blood pressure, heart rate, and cardiac output. Consequently, a significant proportion of patients continue to experience chronic angina despite treatment, increasing the risk of future heart issues. Several clinical studies, including the Total Ischemic Burden European Trial (TIBET), International Multicenter Angina Exercise (IMAGE) study, Combination of Trimetazidine with Metoprolol in stable effort Angina, Poland (TRIMPOL II) study, and Trimetazidine in Angina Combination Therapy (TACT) study, have reported conflicting findings regarding the efficacy of combination therapy with two hemodynamic agents. However, previous research suggests that combining Trimetazidine with beta blockers or long-acting nitrates can lead to significant improvements in exercise stress test parameters and better management of uncontrolled anginal symptoms, with good patient tolerability. This study aims to explore the potential of metabolic therapy, exemplified by the combination of Trimetazidine with Metoprolol, as a contemporary approach to ischemic illnesses. The lack of unique dosage forms and comprehensive research investigations underpinning this combination make them promising candidates for further investigation in this study.

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Herbal medicine for inflammatory bowel diseases: development of pattern identification algorithms by retrospective analysis of case series data

Cited by 6 publications

References 39 publications

The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review

The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review

Prediction of Clinical Remission with Adalimumab Therapy in Patients with Ulcerative Colitis by Fourier Transform–Infrared Spectroscopy Coupled with Machine Learning Algorithms

Pharmacological Profiling and Therapeutic Evaluation of Herbal Plants in Inflammatory Bowel Disease Management

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