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Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
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Non-equilibrium in the Cell01:16

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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Prescription, Nonprescription and Orphan Drugs01:02

Prescription, Nonprescription and Orphan Drugs

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Prescription drugs require a prescription from a medical practitioner and can only be obtained from a pharmacy. They have many applications, including treating pain, anxiety, and hypertension.
The misuse and addiction to prescription drugs is a growing problem that can affect people of all age groups, specifically teenagers. This can happen when prescription medications are used in ways not intended by the prescriber, such as taking someone else's prescription or using medication for...
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Drug Dosage Regimen: Overview01:15

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A drug dosage regimen describes the specific instructions and schedule for administering a drug to a patient. It considers factors such as drug dosage, frequency, route of administration, and duration of treatment. Designing an appropriate dosage regimen for a patient aims to achieve a target drug concentration at the site of action.
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Drugs Affecting Neurotransmitter Synthesis01:29

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Drugs affecting neurotransmitter synthesis can impact the adrenergic neuron and the synthesis of neurotransmitters. For example, α-methyltyrosine and carbidopa target specific enzymes involved in catecholamine synthesis. α-methyltyrosine inhibits the enzyme tyrosine hydroxylase, which converts tyrosine into dopamine. By blocking this enzyme, α-methyltyrosine reduces dopamine production and other catecholamines. Carbidopa, on the other hand, inhibits the enzyme dopa decarboxylase,...
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Drugs Acting on Autonomic Ganglia: Stimulants01:23

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Ganglionic stimulants activate NM nicotinic receptors in autonomic ganglia, falling into two categories: nicotine mimetics [e.g., lobeline, dimethylpiperazine, tetramethylammonium] and muscarinic receptor agonists [e.g., muscarine, methacholine]. The first category's action is rapid and blocked by nicotinic receptor antagonists, while the second category's action is delayed and blocked by atropine-like agents. Nicotine, an alkaloid, affects the heart rate by stimulating...
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相关实验视频

Updated: Sep 12, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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从使用Gen-AI到个性化药物说明书的初步结果.

Joao Almeida1,2, Catherine Chronaki1, Anne Moen3

  • 1HL7 Europe, Brussels, Belgium.

Studies in health technology and informatics
|August 8, 2025
PubMed
概括
此摘要是机器生成的。

大型语言模型 (LLM) 可以从健康记录中创建个性化的患者信息传单 (PIL) 摘要. 需要进一步的研究来提高准确性和个性化,以便更好地遵守药物治疗.

关键词:
电子健康记录电子健康记录基因人工智能 (Gen-AI) 是一种人工智能.在 HL7 FHIR 中.国际患者汇总报告大型语言模型互操作性互操作性互操作性的互操作性药物治疗 药物治疗个性化个性化个性化

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科学领域:

  • 医疗信息学 医疗信息学
  • 人工智能在医学中的应用

背景情况:

  • 传统的患者信息传单 (PIL) 是静态的,通常难以理解.
  • 欧洲药物管理局 (EMA) 正在使用HL7 FHIR®标准转向电子产品信息 (ePI).
  • 个性化医疗需要量身定制的患者信息,以提高理解和遵守.

研究的目的:

  • 探索大型语言模型 (LLM) 的潜力,以生成个性化的PIL摘要.
  • 评估使用国际患者摘要 (IPS) 数据来定制药物信息的可行性.
  • 通过简化,个性化的PIL内容来增强患者的理解和坚持.

主要方法:

  • 使用三个开源LLM进行实验,以生成PIL摘要.
  • 使用带有和没有个性化的提示,以IPS数据为指导.
  • 评估LLM生成的摘要的连贯性,准确性和个性化.

主要成果:

  • LLM 证明了能够生成 PIL 的连贯摘要的能力.
  • 目前的LLM输出需要提高准确性和个性化.
  • 个性化的PIL显示出增强患者与医生的沟通和共享决策的潜力.

结论:

  • LLM提供了一个有前途的途径,用于创建个性化的患者信息.
  • 进一步开发快速工程和模型微调对于临床应用至关重要.
  • 个性化的PIL可以支持共享决策,并改善患者对治疗的参与度.