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Related Concept Videos

Clinical Trials01:16

Clinical Trials

6.7K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
128
Nursing Interventions II: Selecting and Classifying the Nursing Interventions01:29

Nursing Interventions II: Selecting and Classifying the Nursing Interventions

2.2K
Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
2.2K
Pharmacovigilance01:19

Pharmacovigilance

833
Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
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Data Validation01:03

Data Validation

5.0K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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[Implementing new interventions and indications: the possible role for real world data].

J L P Kuijpens1, Tjerk Heimens Visser2, Andre Dekker3,4

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Artificial intelligence (AI) can aid clinical decisions when randomized clinical trials (RCTs) are unavailable. This article explores AI

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Area of Science:

  • Oncology
  • Radiotherapy
  • Health Informatics

Context:

  • Clinical decision-making relies on predicting intervention outcomes and side effects.
  • Randomized clinical trials (RCTs) are often lacking or inconclusive for specific patient therapies.
  • Artificial intelligence (AI) utilizing real-world data (RWD) offers potential for clinical decision support.

Purpose:

  • To present a joint opinion from a radiotherapy facility and health insurers on the role of AI in clinical decision-making.
  • To explore the application of AI using RWD to aid treatment choices when RCT evidence is insufficient.
  • To use the introduction of proton radiotherapy in The Netherlands as a case study for AI-driven decision-making.

Summary:

  • AI algorithms leveraging RWD can assist clinicians when RCT evidence is limited.
  • A radiotherapy center and health insurers discuss AI's potential in guiding therapy selection.
  • The use of AI for clinical decision support is examined using proton radiotherapy as a model.

Impact:

  • Facilitating informed clinical decisions in the absence of robust RCT evidence.
  • Potentially improving patient outcomes by optimizing therapy selection through AI.
  • Guiding the integration of AI-based tools into routine clinical practice for radiotherapy.