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Related Concept Videos

Healthcare Agencies II01:17

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There are various healthcare agencies in the United States—some of which are managed by religious institutions and others by different government branches.
Parish nursing is a growing specialty nursing profession that focuses on holistic healthcare, health promotion, and illness prevention. It blends professional nursing practice with a health ministry, focusing on health and healing within the context of a Christian community. Parish nurses serve as health educators, referral sources,...
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Secondary Healthcare System01:11

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Secondary healthcare is offered by a specialist, generally in hospitals or clinics for patients referred by primary healthcare providers. It occurs when a person has an illness or injury that requires specific medical care. Secondary care is often referred to as acute care. Secondary care can range from uncomplicated care to repair a minor laceration or treat a strep throat infection to more complicated emergent care, such as treating a head injury sustained in an automobile accident. Whatever...
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Specialized care provided over an extended period is called tertiary care. Usually, a primary or secondary care physician will refer a patient to tertiary care. A patient's maximum physical and mental function is restored in tertiary care, which is caused due to the impact of a chronic illness or condition. Tertiary care aims to achieve the highest level of functioning possible while managing chronic illness. For example, a patient who falls and fractures their hip will need secondary care...
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Healthcare agencies provide healthcare services to people. In the United States, voluntary agencies are often non-profit centers sponsored by donations, grants, or fundraisers. One such organization is Meals on Wheels, which provides meals to the elderly and homebound. The American Heart Association and the American Lung Association are other non-profit community organizations. Doctors and nurses are frequently active members of these organizations, which offer health checks and educational...
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An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
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Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
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A guide to deep learning in healthcare.

Andre Esteva1, Alexandre Robicquet2, Bharath Ramsundar2

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Deep learning techniques are revolutionizing healthcare by enhancing medical imaging, electronic health records, robotic surgery, and genomics. These advanced computational methods offer new ways to build impactful end-to-end medical systems.

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Area of Science:

  • Computational Medicine
  • Artificial Intelligence in Healthcare

Background:

  • Deep learning is a subset of machine learning that uses neural networks with multiple layers to analyze complex data.
  • The application of AI in healthcare is rapidly expanding, offering potential for significant advancements.

Purpose of the Study:

  • To present deep-learning techniques applicable to various healthcare domains.
  • To explore the impact of deep learning on medicine and the development of integrated systems.

Main Methods:

  • Focus on deep learning in computer vision for medical imaging analysis.
  • Application of natural language processing to electronic health record data.
  • Discussion of reinforcement learning in robotic-assisted surgery.
  • Review of generalized deep learning methods for genomics.

Main Results:

  • Deep learning in computer vision can enhance medical image interpretation.
  • Natural language processing can extract valuable information from electronic health records.
  • Reinforcement learning shows promise in improving robotic-assisted surgical procedures.
  • Generalized deep learning methods offer new avenues for genomic data analysis.

Conclusions:

  • Deep learning techniques offer transformative potential across diverse medical fields.
  • The integration of these computational methods can lead to more effective end-to-end healthcare solutions.
  • Further research and development in deep learning are crucial for advancing medical science and patient care.