Advances and opportunities in the new digital era of telemedicine, e-health, artificial intelligence, and beyond

Wang, Harry HX; Li, Yu-ting; Huang, Junjie; Huang, Wenyong; Wong, Martin CS

doi:10.12809/hkmj235152

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…With the advent of information and the digital era, the identification analysis of herbal medicine will inevitably develop in the direction of quick digital identification at the individual level, which is conducive to the breakthrough of rapid detection technology. , Under the background of digital identification, in this paper, the “digital identities” of ASR and APR were based on the shared MS data of the same herbs from multiple batches. They had a specific representation, which can provide a reference for establishing the “digital identity” of herbs and provides a way to realize the digital identification of herbs.…”

Section: Resultsmentioning

confidence: 99%

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis

Wang,

Zhang,

et al. 2024

J. Am. Soc. Mass Spectrom.

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Angelicae sinensis radix (ASR) and Angelicae pubescentis radix (APR), as traditional herbal medicines, are often confused and doped in the material market. However, the traditional identification method is to characterize the whole herb with a single or a few components, which do not have representation and cannot realize the effective utilization of unknown components. Consequently, the result is not convincing. In addition, the whole process is time-consuming and labor-intensive. To avoid the confusion and adulteration of ASR and APR as well as to strengthen quality control and improve identification efficiency, in this study, a UHPLC-QTOF-MS E method was used to analyze ASR and APR. Based on digital representation, the shared data with high ionic strength were extracted from different batches of the same herbal medicine as their "digital identity". Further, the above "digital identity" was used as the benchmark for matching and identifying unknown samples to feedback on matching credibility (MC). The results showed that based on the "digital identities" of ASR and APR, the digital identification of two herbal samples can be realized efficiently and accurately at the individual level. And the matching credibility (MC) was higher than 94.00%, even if only 1% of APR or ASR in the mixed samples can still be identified efficiently and accurately. The study is of great practical significance for improving the efficiency of the identification of ASR and APR, cracking down on adulterated and counterfeit drugs, and strengthening the quality control of ASR and APR. In addition, it has important reference significance for developing nontargeted digital identification of herbal medicines at the individual level based on UHPLC-QTOF-MS E and "digital identity", which is beneficial to the construction of digital Chinese medicine and digital quality control.

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Section: Resultsmentioning

confidence: 99%

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis

Wang,

Zhang,

et al. 2024

J. Am. Soc. Mass Spectrom.

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Advancing Telemedicine With Artificial Intelligence (AI)

Swathi,

Das Mohapatra

2024

Advances in Medical Technologies and Clinical Practice

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The convergence of telemedicine and artificial intelligence (AI) technology has ushered in a transformative era in pharmacology. AI algorithms, capable of analysing extensive patient data, enable early detection of deterioration, timely intervention, accurate predictions, and personalized treatment recommendations. This chapter examines the exponential growth of AI technology and its integration into pharmacology, offering insights into decision-making processes surrounding the adoption, implementation, and scaling of AI-driven telemedicine solutions. Through a comprehensive review, it underscores the benefits of AI-based pharma core technology integration into telemedicine, supported by keyword analysis from the Web of Science database. The study concludes that the fusion of pharmacology and AI represents a progressive advancement, particularly in biochemistry, medicine, and health sectors.

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Advances and opportunities in the new digital era of telemedicine, e-health, artificial intelligence, and beyond

Cited by 2 publications

References 16 publications

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis

Advancing Telemedicine With Artificial Intelligence (AI)

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Advances and opportunities in the new digital era of telemedicine, e-health, artificial intelligence, and beyond

Cited by 2 publications

References 16 publications

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MSE Analysis

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MSE Analysis

Advancing Telemedicine With Artificial Intelligence (AI)

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Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis

Identification Analysis of Angelicae sinensis radix and Angelicae pubescentis radix Based on Quantized “Digital Identity” and UHPLC-QTOF-MS^E Analysis