Corrigendum to “Mechanism and Prevention of Atrial Remodeling and Their Related Genes in Cardiovascular Disorders” [Curr Probl Cardiol 2023;48:101414]

Bhushan, Shanti; Ding, Weihao; Huang, Xin; Wu, Qinghui; Su, Xiufang; Gao, Ke; Xiao, Zhi

doi:10.1016/j.cpcardiol.2022.101514

Cited by 2 publications

(2 citation statements)

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“…Recently, 2 manuscripts were published for cardiologist on relevant aspects of AI and machine learning in clinical practice, listing applications and methods to date, and describing how cardiovascular medicine could incorporate AI in the future. 3,25 Undoubtedly, AI holds promise of delivering truly individualized medicine for cardiology. We see the same trend for other medical specialties as well, such as oncology, [26][27][28][29][30] otolaryngology, 31 dermatology, 32 psychiatry, 33 and plastic surgery.…”

Section: Ai In Biomedical Researchmentioning

confidence: 99%

Exploring the Promise and Challenges of Artificial Intelligence in Biomedical Research and Clinical Practice

Altara,

Basson,

Biondi-Zoccai

et al. 2024

Journal of Cardiovascular Pharmacology

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Artificial intelligence (AI) is poised to revolutionize how science, and biomedical research in particular, are done. With AI, problem solving and complex tasks using massive data sets can be performed at a much higher rate and dimensionality level compared to humans. With the ability to handle huge data sets and self-learn, AI is already being exploited in drug design, drug repurposing, toxicology, and material identification. AI could also be used in both basic and clinical research in study design, defining outcomes, analyzing data, interpreting findings, and even identifying the most appropriate areas of investigation and funding sources. State-of-the-art AI-based large language models (LLM), such as ChatGPT and Perplexity, are positioned to change forever how science is communicated and how scientists interact with one another and their profession, including post-publication appraisal and critique. Like all revolutions, upheaval will follow and not all outcomes can be predicted, necessitating guardrails at the onset, especially to minimize the untoward impact of the many drawbacks of LLMs, which include lack of confidentiality, risk of hallucinations, and propagation of mainstream albeit potentially mistaken opinions and perspectives. In this review, we highlight areas of biomedical research that are already being reshaped by AI and how AI is likely to impact it further in the near future. We discuss the potential benefits of AI in biomedical research and address possible risks, some surrounding the creative process, that warrant further reflection.

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Section: Ai In Biomedical Researchmentioning

confidence: 99%

Exploring the Promise and Challenges of Artificial Intelligence in Biomedical Research and Clinical Practice

Altara,

Basson,

Biondi-Zoccai

et al. 2024

Journal of Cardiovascular Pharmacology

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“…The heart is supplied with more oxygen and blood when blood pressure is lowered. 35 The detection of VAL is crucial in various domains of society and can be utilized to further evaluate a patient seeking assessment. Numerous techniques (spectroscopic, electrochemical and chromatographic methods) have been documented for the quantification of VAL in biological fluids, pharmacological preparations and bulk forms.…”

Section: Introductionmentioning

confidence: 99%

Hydrothermal synthesis of modified lignin-based carbon dots derived from biomass waste for fluorescence determination of valsartan

Aldakhil,

Alarfaj,

Al-Tamimi

et al. 2024

RSC Adv.

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Corrigendum to “Mechanism and Prevention of Atrial Remodeling and Their Related Genes in Cardiovascular Disorders” [Curr Probl Cardiol 2023;48:101414]

Cited by 2 publications

References 0 publications

Exploring the Promise and Challenges of Artificial Intelligence in Biomedical Research and Clinical Practice

Exploring the Promise and Challenges of Artificial Intelligence in Biomedical Research and Clinical Practice

Hydrothermal synthesis of modified lignin-based carbon dots derived from biomass waste for fluorescence determination of valsartan

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