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Sampling Plans01:23

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
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The planning phase of the nursing process helps nurses set priorities, outline patient-centered goals and expected outcomes, and tailor nursing interventions to align with the aligned care plan. Through the planning phase, the nurse applies critical thinking skills to align and develop interventions according to the patient's needs. It provides continuity of care allowing patients to receive the maximum benefit from treatment. It serves as a pilot plan for allocating individual staff to a...
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A nursing care plan can present in two forms: informal and formal. Informal is a care plan for the individual use of the nurse and goals they wish to accomplish during their shift. Informal care plans are not included in the patient chart. A formal nursing care plan is a written or computerized guide that organizes patient care. It is further subdivided into two: standardized and individualized care plans. Standardized care plans are pre-populated care plans for specific patient populations,...
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Several factors are considered while creating a patient's care plan. Motivation is a factor in improving communication, and patients often require encouragement to try different approaches involving significant change. It is essential to involve the patient and family in decisions about the plan of care to determine whether the suggested methods are acceptable. Consider meeting critical comfort and safety needs before introducing new communication methods and techniques. Allow adequate time...
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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
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Automated 4π radiotherapy treatment planning with evolving knowledge-base.

Angelia Landers1, Daniel O'Connor1, Dan Ruan1

  • 1Department of Radiation Oncology, University of California, Los Angeles, CA, 90095, USA.

Medical Physics
|June 25, 2019
PubMed
Summary

Automated 4π radiotherapy planning using evolving knowledge-base (EKB) planning improved plan quality by guiding beam selection with dose prediction. This novel technique enhances organ-at-risk sparing and optimizes treatment plans.

Keywords:
4πautomated treatment planningevolution

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Non-coplanar 4π radiotherapy automates beam selection but requires complex tuning for optimal plan quality.
  • Existing methods can be tedious and yield inconsistent results, necessitating more efficient automated solutions.

Purpose of the Study:

  • To develop a fully automated 4π radiotherapy treatment planning system using evolving knowledge-base (EKB) planning guided by dose prediction.
  • To improve organ-at-risk (OAR) sparing and overall plan quality in automated radiotherapy planning.

Main Methods:

  • A statistical voxel dose learning model was trained on initial low-quality plans.
  • A novel 4π optimization problem incorporated a one-sided penalty on OAR dose deviation from predicted doses.
  • The fast iterative shrinkage-thresholding algorithm (FISTA) was employed for optimization over 10 EKB planning loops.

Main Results:

  • EKB plans showed significantly higher plan quality metrics (PQM) for lung cases compared to manually created 4π plans.
  • Head and Neck (HN) EKB plans achieved comparable quality to manual 4π plans but were surpassed by automated plans using high-quality training data.
  • While individually evolved plans showed improvement, many were trapped in local minima, unlike the EKB approach.

Conclusions:

  • Evolving knowledge-base planning offers a novel automated workflow for radiotherapy, leveraging predicted dose distributions to enhance plan quality.
  • This technique can evolve from initially low-quality plans and effectively incorporate new beams for superior treatment outcomes.