BACKGROUND Medication errors,especially in dosage calculation,pose risks in healthcare.Artificial intelligence(AI)systems like ChatGPT and Google Bard may help reduce errors,but their accuracy in providing medication ...BACKGROUND Medication errors,especially in dosage calculation,pose risks in healthcare.Artificial intelligence(AI)systems like ChatGPT and Google Bard may help reduce errors,but their accuracy in providing medication information remains to be evaluated.AIM To evaluate the accuracy of AI systems(ChatGPT 3.5,ChatGPT 4,Google Bard)in providing drug dosage information per Harrison's Principles of Internal Medicine.METHODS A set of natural language queries mimicking real-world medical dosage inquiries was presented to the AI systems.Responses were analyzed using a 3-point Likert scale.The analysis,conducted with Python and its libraries,focused on basic statistics,overall system accuracy,and disease-specific and organ system accuracies.RESULTS ChatGPT 4 outperformed the other systems,showing the highest rate of correct responses(83.77%)and the best overall weighted accuracy(0.6775).Disease-specific accuracy varied notably across systems,with some diseases being accurately recognized,while others demonstrated significant discrepancies.Organ system accuracy also showed variable results,underscoring system-specific strengths and weaknesses.CONCLUSION ChatGPT 4 demonstrates superior reliability in medical dosage information,yet variations across diseases emphasize the need for ongoing improvements.These results highlight AI's potential in aiding healthcare professionals,urging continuous development for dependable accuracy in critical medical situations.展开更多
Systemic abnormalities often occur in patients with liver disease. In particular, cardiopulmonary or renal diseases accompanied by advanced liver disease can be serious and may determine the quality of life and progno...Systemic abnormalities often occur in patients with liver disease. In particular, cardiopulmonary or renal diseases accompanied by advanced liver disease can be serious and may determine the quality of life and prognosis of patients. Therefore, both hepatologists and non-hepatologists should pay attention to such abnormalities in the management of patients with liver diseases.展开更多
Hemoglobin-styrene oxide adducts in blood have been studied as a molecular biomarker of worker exposed to styrene. Determination of protein-styrene oxide adducts in different biological samples with modified Raney-Ni ...Hemoglobin-styrene oxide adducts in blood have been studied as a molecular biomarker of worker exposed to styrene. Determination of protein-styrene oxide adducts in different biological samples with modified Raney-Ni procedure is described in this paper. The following biological samples have been investigated: fresh rat blood reacted with styrene oxide in vitro: rat blood reacted with styrene or styrene oxide in vivo: vein blood from workers exposed to styrene in two factories. The data showed that there was a good linear dose-response relationship between reacting dose of styrene oxide or styrene and amount of protein-styrene oxide adducts in both in vitro and in vivo experiments. For human samples, a dose-response relationship between protein adducts and styrene exposure can be found in glass fiber factory, but not in piano manufacture plant.展开更多
文摘BACKGROUND Medication errors,especially in dosage calculation,pose risks in healthcare.Artificial intelligence(AI)systems like ChatGPT and Google Bard may help reduce errors,but their accuracy in providing medication information remains to be evaluated.AIM To evaluate the accuracy of AI systems(ChatGPT 3.5,ChatGPT 4,Google Bard)in providing drug dosage information per Harrison's Principles of Internal Medicine.METHODS A set of natural language queries mimicking real-world medical dosage inquiries was presented to the AI systems.Responses were analyzed using a 3-point Likert scale.The analysis,conducted with Python and its libraries,focused on basic statistics,overall system accuracy,and disease-specific and organ system accuracies.RESULTS ChatGPT 4 outperformed the other systems,showing the highest rate of correct responses(83.77%)and the best overall weighted accuracy(0.6775).Disease-specific accuracy varied notably across systems,with some diseases being accurately recognized,while others demonstrated significant discrepancies.Organ system accuracy also showed variable results,underscoring system-specific strengths and weaknesses.CONCLUSION ChatGPT 4 demonstrates superior reliability in medical dosage information,yet variations across diseases emphasize the need for ongoing improvements.These results highlight AI's potential in aiding healthcare professionals,urging continuous development for dependable accuracy in critical medical situations.
文摘Systemic abnormalities often occur in patients with liver disease. In particular, cardiopulmonary or renal diseases accompanied by advanced liver disease can be serious and may determine the quality of life and prognosis of patients. Therefore, both hepatologists and non-hepatologists should pay attention to such abnormalities in the management of patients with liver diseases.
基金TheNationalNaturalScienceFoundationofChina (No .5 98730 2 8)
文摘Hemoglobin-styrene oxide adducts in blood have been studied as a molecular biomarker of worker exposed to styrene. Determination of protein-styrene oxide adducts in different biological samples with modified Raney-Ni procedure is described in this paper. The following biological samples have been investigated: fresh rat blood reacted with styrene oxide in vitro: rat blood reacted with styrene or styrene oxide in vivo: vein blood from workers exposed to styrene in two factories. The data showed that there was a good linear dose-response relationship between reacting dose of styrene oxide or styrene and amount of protein-styrene oxide adducts in both in vitro and in vivo experiments. For human samples, a dose-response relationship between protein adducts and styrene exposure can be found in glass fiber factory, but not in piano manufacture plant.
