Effectiveness of ChatGPT in clinical pharmacy and the role of artificial intelligence in medication therapy management

Roosan, Don; Padua, Pauline; Khan, Raiyan; Khan, Hasiba; Verzosa, Claudia; Wu, Yanting

doi:10.1016/j.japh.2023.11.023

Cited by 26 publications

(3 citation statements)

References 22 publications

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“…and behavioral profiles hold enormous promise. Well-designed trials like the WeChat smoking cessation study will provide vital evidence on innovative interventions like integrated mobile cessation modalities(Roosan et al 2023;Chu et al 2023). Findings from emerging directions can inform continued optimization of established cessation approaches.…”

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confidence: 99%

Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting

Addissouky,

El Sayed,

Ali

et al. 2024

Bull Natl Res Cent

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Background Tobacco smoking remains a major preventable cause of disease and death worldwide. Combustible cigarettes release thousands of chemicals that can initiate inflammatory pathways leading to smoking-related illness. This review aims to synthesize current scientific knowledge on mechanisms of smoking-induced disease, epidemiological trends, and clinical strategies from recent literature. Main body of the abstract At the cellular level, cigarette smoke triggers oxidative stress through reactive oxygen species (ROS), causing DNA damage. This provokes inflammatory signaling cascades mediated by damage-associated molecular patterns (DAMPs), receptors like RAGE and TLRs, and downstream cytokines. Smoking also disrupts apoptosis and autophagy. In the lungs, oxidative stress and inflammation from smoking play central roles in COPD pathogenesis. Smoking-induced oxidative DNA damage, chronic inflammation, and impaired immunity combine to promote lung carcinogenesis. For cardiovascular disease, smoking triggers endothelial dysfunction, platelet activation, and atherogenesis through oxidized LDL and effects on nitric oxide and adhesion molecules. Short conclusion Given the unequivocal evidence of health risks, smoking cessation is critical to reducing preventable death and disability. Both counseling and pharmacotherapy have proven efficacy for quitting, but efficacy remains limited long-term. Emerging nicotine products like e-cigarettes have unknown impacts on cessation and population health. Comprehensive efforts encompassing prevention, screening, treatment innovation, harm reduction, and policy reform focused on curbing smoking-attributable morbidity and mortality are warranted.

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mentioning

confidence: 99%

Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting

Addissouky,

El Sayed,

Ali

et al. 2024

Bull Natl Res Cent

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“…Machine learning has found applications in tasks such as medical imaging, disease diagnosis, patient prognosis, and treatment decision-making [26][27][28]. Moreover, AI has been successfully integrated into other important aspects of healthcare such as virtual nursing assistants and reducing medication errors [29]. As shown in Table 2, the majority of AI applications are within the medical field due to several key factors that must be addressed for optimal patient care outcomes.…”

Section: Key Applications Of Ai In Healthcarementioning

confidence: 99%

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Bekbolatova,

Mayer,

Ong

et al. 2024

Healthcare

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Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing healthcare delivery. By harnessing machine learning algorithms, natural language processing, and computer vision, AI enables the analysis of complex medical data. The integration of AI into healthcare systems aims to support clinicians, personalize patient care, and enhance population health, all while addressing the challenges posed by rising costs and limited resources. As a subdivision of computer science, AI focuses on the development of advanced algorithms capable of performing complex tasks that were once reliant on human intelligence. The ultimate goal is to achieve human-level performance with improved efficiency and accuracy in problem-solving and task execution, thereby reducing the need for human intervention. Various industries, including engineering, media/entertainment, finance, and education, have already reaped significant benefits by incorporating AI systems into their operations. Notably, the healthcare sector has witnessed rapid growth in the utilization of AI technology. Nevertheless, there remains untapped potential for AI to truly revolutionize the industry. It is important to note that despite concerns about job displacement, AI in healthcare should not be viewed as a threat to human workers. Instead, AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks. By automating routine and repetitive tasks, AI can alleviate the burden on healthcare professionals, allowing them to dedicate more attention to patient care and meaningful interactions. However, legal and ethical challenges must be addressed when embracing AI technology in medicine, alongside comprehensive public education to ensure widespread acceptance.

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“…This application of AI not only streamlines MTM processes but also leverages the vast amount of medical knowledge available to improve patient care. In simpler terms, AI, like ChatGPT, can help healthcare providers identify and address medication issues faster and more accurately, ultimately leading to better patient outcomes [ 4 ]. ChatGPT offers precise and current details on medications, covering aspects like dosages, purposes, potential side effects (ADR), interactions with other drugs, and even cost information.…”

Section: Introductionmentioning

confidence: 99%

Causality Assessment of Adverse Drug Reaction Toxic Epidermal Necrolysis With the Aid of ChatGPT: A Case Report

Pandya,

Patel,

Sojitra

et al. 2024

Cureus

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Toxic epidermal necrolysis (TEN) is a severe and potentially fatal adverse drug reaction. This case report presents a 19-year-old male with pulmonary tuberculosis undergoing anti-tubercular therapy who developed TEN. The patient had multiple comorbidities including type 1 diabetes mellitus and multisystem atrophy. ChatGPT was utilized alongside conventional methods to assess causality. While conventional scoring systems estimated mortality at 58.3% (SCORTEN) and 12.3% (ABCD-10), ChatGPT yielded divergent scores. Causality assessment using WHO-Uppsala Monitoring Centre (UMC) and Naranjo's scale indicated rifampicin and isoniazid as probable causative agents. However, ChatGPT provided ambiguous results. The study underscores the potential of AI in pharmacovigilance but emphasizes caution due to discrepancies observed. Collaborative utilization of artificial intelligence (AI) with clinical judgment is advocated to enhance diagnostic accuracy and treatment decisions in adverse drug reactions. This case highlights the importance of integrating AI into drug safety systems while acknowledging its limitations to ensure optimal patient care.

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Effectiveness of ChatGPT in clinical pharmacy and the role of artificial intelligence in medication therapy management

Cited by 26 publications

References 22 publications

Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting

Oxidative stress and inflammation: elucidating mechanisms of smoking-attributable pathology for therapeutic targeting

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Causality Assessment of Adverse Drug Reaction Toxic Epidermal Necrolysis With the Aid of ChatGPT: A Case Report

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