The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Background: Procalcitonin (PCT) is a crucial biomarker for diagnosing sepsis and managing antibiotic therapy. This study evaluated the analytical performance and comparability of the Access PCT and Elecsys BRAHMS PCT assays. Methods: The precision, detection capability, linearity, and reference range of both assays were assessed. A comparative analysis included 182 patient samples categorized into four risk groups to compare the results between Access PCT and Elecsys BRAHMS PCT assays. Results: The Access PCT assay demonstrated precision within the manufacturer’s threshold, and its detection capabilities were verified. This assay exhibited excellent linearity and appropriate reference intervals. Comparative analysis indicated that the Access PCT assay reported higher overall PCT levels than the Elecsys BRAHMS assay, with high agreement between the assays (κ=0.941). However, the biases varied across different PCT concentration intervals. Conclusions Both the Access PCT and Elecsys BRAHMS PCT assays performed robustly with notable concordance but varying biases at different concentration intervals. The observed biases require careful consideration in clinical decision-making, especially when adopting novel assay systems. Standardizing the calibration across different platforms is recommended to improve assay comparability.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Background: Procalcitonin (PCT) is a crucial biomarker for diagnosing sepsis and managing antibiotic therapy. This study evaluated the analytical performance and comparability of the Access PCT and Elecsys BRAHMS PCT assays. Methods: The precision, detection capability, linearity, and reference range of both assays were assessed. A comparative analysis included 182 patient samples categorized into four risk groups to compare the results between Access PCT and Elecsys BRAHMS PCT assays. Results: The Access PCT assay demonstrated precision within the manufacturer’s threshold, and its detection capabilities were verified. This assay exhibited excellent linearity and appropriate reference intervals. Comparative analysis indicated that the Access PCT assay reported higher overall PCT levels than the Elecsys BRAHMS assay, with high agreement between the assays (κ=0.941). However, the biases varied across different PCT concentration intervals. Conclusions Both the Access PCT and Elecsys BRAHMS PCT assays performed robustly with notable concordance but varying biases at different concentration intervals. The observed biases require careful consideration in clinical decision-making, especially when adopting novel assay systems. Standardizing the calibration across different platforms is recommended to improve assay comparability.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Background: Procalcitonin (PCT) is a crucial biomarker for diagnosing sepsis and managing antibiotic therapy. This study evaluated the analytical performance and comparability of the Access PCT and Elecsys BRAHMS PCT assays. Methods: The precision, detection capability, linearity, and reference range of both assays were assessed. A comparative analysis included 182 patient samples categorized into four risk groups to compare the results between Access PCT and Elecsys BRAHMS PCT assays. Results: The Access PCT assay demonstrated precision within the manufacturer’s threshold, and its detection capabilities were verified. This assay exhibited excellent linearity and appropriate reference intervals. Comparative analysis indicated that the Access PCT assay reported higher overall PCT levels than the Elecsys BRAHMS assay, with high agreement between the assays (κ=0.941). However, the biases varied across different PCT concentration intervals. Conclusions Both the Access PCT and Elecsys BRAHMS PCT assays performed robustly with notable concordance but varying biases at different concentration intervals. The observed biases require careful consideration in clinical decision-making, especially when adopting novel assay systems. Standardizing the calibration across different platforms is recommended to improve assay comparability.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Background: Procalcitonin (PCT) is a crucial biomarker for diagnosing sepsis and managing antibiotic therapy. This study evaluated the analytical performance and comparability of the Access PCT and Elecsys BRAHMS PCT assays. Methods: The precision, detection capability, linearity, and reference range of both assays were assessed. A comparative analysis included 182 patient samples categorized into four risk groups to compare the results between Access PCT and Elecsys BRAHMS PCT assays. Results: The Access PCT assay demonstrated precision within the manufacturer’s threshold, and its detection capabilities were verified. This assay exhibited excellent linearity and appropriate reference intervals. Comparative analysis indicated that the Access PCT assay reported higher overall PCT levels than the Elecsys BRAHMS assay, with high agreement between the assays (κ=0.941). However, the biases varied across different PCT concentration intervals. Conclusions Both the Access PCT and Elecsys BRAHMS PCT assays performed robustly with notable concordance but varying biases at different concentration intervals. The observed biases require careful consideration in clinical decision-making, especially when adopting novel assay systems. Standardizing the calibration across different platforms is recommended to improve assay comparability.

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Background: Procalcitonin (PCT) is a crucial biomarker for diagnosing sepsis and managing antibiotic therapy. This study evaluated the analytical performance and comparability of the Access PCT and Elecsys BRAHMS PCT assays. Methods: The precision, detection capability, linearity, and reference range of both assays were assessed. A comparative analysis included 182 patient samples categorized into four risk groups to compare the results between Access PCT and Elecsys BRAHMS PCT assays. Results: The Access PCT assay demonstrated precision within the manufacturer’s threshold, and its detection capabilities were verified. This assay exhibited excellent linearity and appropriate reference intervals. Comparative analysis indicated that the Access PCT assay reported higher overall PCT levels than the Elecsys BRAHMS assay, with high agreement between the assays (κ=0.941). However, the biases varied across different PCT concentration intervals. Conclusions Both the Access PCT and Elecsys BRAHMS PCT assays performed robustly with notable concordance but varying biases at different concentration intervals. The observed biases require careful consideration in clinical decision-making, especially when adopting novel assay systems. Standardizing the calibration across different platforms is recommended to improve assay comparability.