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Related Concept Videos

Dementia01:30

Dementia

534
Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
534
Nursing Diagnosis01:22

Nursing Diagnosis

3.7K
Following assessment, a nursing diagnosis is the next step in the nursing process. It begins after the nurse has collected and recorded the patient data. The purpose of diagnosing is to identify how the client responds to actual or potential health processes, identify factors that bestow or that cause health problems, the etiologies, and identify resources or strengths the individual, group, or community can draw on to prevent or resolve problems.
The nursing diagnosis focuses on evidence-based...
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Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

1.7K
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
1.7K
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

3.6K
A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains...
3.6K
Diabetes: Symptoms, Diagnosis, and Complications01:15

Diabetes: Symptoms, Diagnosis, and Complications

2.1K
For most patients, experiencing several weeks of polyuria, polydipsia, fatigue, and significant weight loss may indicate the presence of diabetes. Furthermore, adults displaying the phenotypic appearance of type 2 diabetes (particularly those who are obese and not initially insulin-requiring), may have islet cell autoantibodies, suggesting autoimmune-mediated β cell destruction and a diagnosis of latent autoimmune diabetes of adults (LADA). The categorization of glucose homeostasis is...
2.1K
Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

3.6K
Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
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Using Retinal Imaging to Study Dementia
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[Use AI for Dementia Diagnosis].

Shotai Kobayashi1

  • 1Faculty of Medicine, Shimane University.

Brain and Nerve = Shinkei Kenkyu No Shinpo
|July 11, 2019
PubMed
Summary

Artificial intelligence (AI) shows promise for early dementia prediction and prevention by analyzing brain scans and daily life data. This technology aims to identify preclinical dementia risk, focusing on lifestyle factors for proactive health management.

Area of Science:

  • Neurology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Dementia diagnosis remains a significant challenge, with current methods often identifying the condition at later stages.
  • Lifestyle factors are increasingly recognized as crucial in the development of dementia in elderly populations.
  • Existing research highlights the potential of advanced technologies in addressing these diagnostic and preventative gaps.

Purpose of the Study:

  • To explore the application of artificial intelligence (AI) in the early detection and prevention of dementia.
  • To investigate novel AI-driven medical devices for dementia diagnosis.
  • To leverage technology for predicting dementia risk in preclinical stages, linking it to lifestyle interventions.

Main Methods:

  • Voxel-based morphometry analysis of brain atrophy.

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  • Brain network analysis utilizing resting-state functional MRI and diffusion tensor imaging.
  • Development of an "Internet of Things" (IoT) based application for detecting dementia in daily life activities.

    • Main Results:

    • AI-based analysis of brain structure and function shows potential for identifying early signs of dementia.
    • IoT technology offers a novel approach to monitor and detect dementia indicators through everyday activities.
    • Research indicates a strong correlation between lifestyle and dementia risk in the elderly, supporting AI's role in prevention.

    Conclusions:

    • AI is a promising tool for the preclinical diagnosis of dementia, moving beyond definitive diagnosis to risk prediction.
    • The integration of AI with neuroimaging and IoT technologies can lead to innovative medical devices for dementia detection.
    • Focusing on AI for early prediction and prevention, informed by lifestyle data, represents a paradigm shift in dementia care.