Utility of ChatGPT in Clinical Practice Liu, Jialin; Wang, Changyu; Liu, Siru
JMIR. Journal of medical internet research/Journal of medical internet research,
06/2023, Volume:
25, Issue:
1
Journal Article
Peer reviewed
Open access
ChatGPT is receiving increasing attention and has a variety of application scenarios in clinical practice. In clinical decision support, ChatGPT has been used to generate accurate differential ...diagnosis lists, support clinical decision-making, optimize clinical decision support, and provide insights for cancer screening decisions. In addition, ChatGPT has been used for intelligent question-answering to provide reliable information about diseases and medical queries. In terms of medical documentation, ChatGPT has proven effective in generating patient clinical letters, radiology reports, medical notes, and discharge summaries, improving efficiency and accuracy for health care providers. Future research directions include real-time monitoring and predictive analytics, precision medicine and personalized treatment, the role of ChatGPT in telemedicine and remote health care, and integration with existing health care systems. Overall, ChatGPT is a valuable tool that complements the expertise of health care providers and improves clinical decision-making and patient care. However, ChatGPT is a double-edged sword. We need to carefully consider and study the benefits and potential dangers of ChatGPT. In this viewpoint, we discuss recent advances in ChatGPT research in clinical practice and suggest possible risks and challenges of using ChatGPT in clinical practice. It will help guide and support future artificial intelligence research similar to ChatGPT in health.
► The contribution plots without smearing effect on non-faulty variables are given. ► The faulty variables of simple and complex faults can be isolated correctly. ► The process faults, the Tennessee ...Eastman problem, are also dealt with successfully. ► The proposed approach outperformed the alternative missing data approaches is demonstrated.
Isolating faulty variables to provide additional information about a process fault is a crucial step in the diagnosis of a process fault. There are two types of data-driven approaches for isolating faulty variables. One is the supervised method, which requires the datasets of known faults to define a fault subspace or an abnormal operating region for each faulty mode. This type of approach is not practical for an industrial process, since the known event lists might not exist for some industrial processes. The counterpart is to isolate faulty variables without a priori knowledge, using, for example, a contribution plot, which is a popular tool in the unsupervised category. However, it is well known that this approach suffers from the smearing effect, which may mislead the faulty variables of the detected faults. In the presented work, a contribution plot without the smearing effect on non-faulty variables was derived based on missing data analysis. Two benchmark examples, the continuous stirred tank reactor (CSTR) and the Tennessee Eastman (TE) process, were provided to compare the fault isolation performances of the alternatives using the missing data approach.
This paper aims to discuss the effectiveness of financial deleveraging by observing and studying the changes in the scale of shadow banking in China. China’s shadow banking can be divived into two ...parts: intra-bank shadow banking and extra-bank shadow banking, whose scale can be calculated by the indirect method based on the balance sheet and the direct method respectively. Through data statistics and calculations, it is concluded that the scale of shadow banking in China has slowed down since 2017 and started to decline gradually in 2018. In other words, financial deleveraging is effective.
Ethical Considerations of Using ChatGPT in Health Care Wang, Changyu; Liu, Siru; Yang, Hao ...
JMIR. Journal of medical internet research/Journal of medical internet research,
08/2023, Volume:
25, Issue:
1
Journal Article
Peer reviewed
Open access
ChatGPT has promising applications in health care, but potential ethical issues need to be addressed proactively to prevent harm. ChatGPT presents potential ethical challenges from legal, humanistic, ...algorithmic, and informational perspectives. Legal ethics concerns arise from the unclear allocation of responsibility when patient harm occurs and from potential breaches of patient privacy due to data collection. Clear rules and legal boundaries are needed to properly allocate liability and protect users. Humanistic ethics concerns arise from the potential disruption of the physician-patient relationship, humanistic care, and issues of integrity. Overreliance on artificial intelligence (AI) can undermine compassion and erode trust. Transparency and disclosure of AI-generated content are critical to maintaining integrity. Algorithmic ethics raise concerns about algorithmic bias, responsibility, transparency and explainability, as well as validation and evaluation. Information ethics include data bias, validity, and effectiveness. Biased training data can lead to biased output, and overreliance on ChatGPT can reduce patient adherence and encourage self-diagnosis. Ensuring the accuracy, reliability, and validity of ChatGPT-generated content requires rigorous validation and ongoing updates based on clinical practice. To navigate the evolving ethical landscape of AI, AI in health care must adhere to the strictest ethical standards. Through comprehensive ethical guidelines, health care professionals can ensure the responsible use of ChatGPT, promote accurate and reliable information exchange, protect patient privacy, and empower patients to make informed decisions about their health care.
Since online measurement of the melt index (MI) of polyethylene is difficult, a virtual sensor model is desirable. However, a polyethylene process usually produces products with multiple grades. The ...relation between process and quality variables is highly nonlinear. Besides, a virtual sensor model in real plant process with many inputs has to deal with collinearity and time-varying issues. A new recursive algorithm, which models a multivariable, time-varying and nonlinear system, is presented. Principal component analysis (PCA) is used to eliminate the collinearity. Fuzzy c-means (FCM) and fuzzy Takagi–Sugeno (FTS) modeling are used to decompose the nonlinear system into several linear subsystems. Effectiveness of the model is demonstrated using real plant data from a polyethylene process.
A novel hot-press molding method was developed to manufacture all-composite sandwich panel with tetrahedral truss cores in this paper. The out-of-plane compressive and in-plane shear behaviors of ...this structure were investigated by experiments. The results have shown that the tetrahedral truss core sandwich panel had a high compressive specific strength compared to metallic truss core sandwich panels. The node failure was observed in the experimental process. Finite element analysis (FEA) with a progressive failure model was involved to simulate the damage evolution process and predict the mechanical properties. The analytical formulae were also presented to predict the stiffness and strength of sandwich panel. Good agreement was found between FEA calculated results and the experimental results. It is expected that this study can provide useful information for the fabrication and application of all-composite tetrahedral truss core sandwich panel.
The goal of this study is to construct a mortality prediction model using the XGBoot (eXtreme Gradient Boosting) decision tree model for AKI (acute kidney injury) patients in the ICU (intensive care ...unit), and to compare its performance with that of three other machine learning models.
We used the eICU Collaborative Research Database (eICU-CRD) for model development and performance comparison. The prediction performance of the XGBoot model was compared with the other three machine learning models. These models included LR (logistic regression), SVM (support vector machines), and RF (random forest). In the model comparison, the AUROC (area under receiver operating curve), accuracy, precision, recall, and F1 score were used to evaluate the predictive performance of each model.
A total of 7548 AKI patients were analyzed in this study. The overall in-hospital mortality of AKI patients was 16.35%. The best performing algorithm in this study was XGBoost with the highest AUROC (0.796, p < 0.01), F1(0.922, p < 0.01) and accuracy (0.860). The precision (0.860) and recall (0.994) of the XGBoost model rank second among the four models.
XGBoot model had obvious advantages of performance compared to the other machine learning models. This will be helpful for risk identification and early intervention for AKI patients at risk of death.
•D. vulgaris is pre-grown on C1018 carbon steel coupons before the starvation test.•Carbon source starvation weakens the SRB biofilm but still increases weight loss.•Weight loss is 6.6 mg/cm2 for 20% ...carbon source vs. 3.3 mg/cm2 for 100% after 10 d.•Pit depth and electrochemical measurement data corroborate weight loss trend.•Iron corrosion by SRB belongs to extracellular electron transfer MIC (EET-MIC).
Microbiologically influenced corrosion (MIC) of carbon steel by sulfate reducing bacterium (SRB) Desulfovibrio vulgaris under organic carbon starvation was investigated using electrochemical methods to support weight loss and pitting data. 20% carbon source led to the highest weight loss (6.6 mg/cm2), while 100% had the lowest (3.3 mg/cm2) after 10 days. Linear polarization resistance and electrochemical impedance spectrometry data confirmed the weight loss and pitting data trends. The data in this work support the theory that carbon steel corrosion by SRB is due to electron harvest from extracellular iron oxidation by SRB, which belongs to extracellular electron transfer MIC (EET-MIC).
Effective removal of pathogenic bacteria is key to improving the prognosis of sepsis. Polymorphonuclear neutrophils (PMNs) are the most important components of innate cellular immunity and play vital ...roles in clearing pathogenic bacteria. However, the metabolic characteristics and immunomodulatory pathways of PMNs during sepsis have not been investigated. In the present study, we explored the immune metabolism characteristics of PMNs and the mechanism by which neutrophilic glycolysis is regulated during sepsis.
Metabolomics analysis was performed on PMNs isolated from 14 septic patients, 26 patients with acute appendicitis, and 19 healthy volunteers. Transcriptome analysis was performed on the PMNs isolated from the healthy volunteers and the patients with sepsis to assess glycolysis and investigate its mechanism. Lipopolysaccharide (LPS) was used to stimulate the neutrophils isolated from the healthy volunteers at different time intervals to build an LPS-tolerant model. Chemotaxis, phagocytosis, lactate production, oxygen consumption rate (OCR), and extracellular acidification rate (ECAR) were evaluated.
Transcriptomics showed significant changes in glycolysis and the mTOR/HIF-1α signaling pathway during sepsis. Metabolomics revealed that the Warburg effect was significantly altered in the patients with sepsis. We discovered that glycolysis regulated PMNs' chemotaxis and phagocytosis functions during sepsis. Lactate dehydrogenase A (LDHA) downregulation was a key factor in the inhibition of glycolysis in PMNs. This study confirmed that the PI3K/Akt-HIF-1α pathway was involved in the LDHA expression level and also influenced PMNs' chemotaxis and phagocytosis functions.
The inhibition of glycolysis contributed to neutrophil immunosuppression during sepsis and might be controlled by PI3K/Akt-HIF-1α pathway-mediated LDHA downregulation. Our study provides a scientific theoretical basis for the management and treatment of patients with sepsis and promotes to identify therapeutic target for the improvement of immune function in sepsis.
Paddlefish has high economic and ecological value. In this study, microbial diversity and community structure in intestine, stomach, and mouth of paddlefish were detected using high-throughput ...sequencing. The results showed that the diversity and richness indices decreased along the digestive tract, and significantly lower proportion of those were observed in intestine. Firmicutes, Bacteroidetes and Proteobacteria were the dominant phyla. In top 10 phyla, there was no significant difference in mouth and stomach. But compared with intestine, there were significant differences in 8 of the 10 phyla, and Firmicutes and Bacteroidetes increased significantly, while Proteobacteria decreased significantly. There was no dominant genus in mouth and stomach, but Clostridium_sensu_stricto_1 and uncultured_bacterium_o_Bacteroidales was predominant in intestine. In conclusion, the species and abundance of microbiota in the mouth and stomach of paddlefish were mostly the same, but significantly different from those in intestine. Moreover, there was enrichment of the dominant bacteria in intestine.
PDF
