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相关概念视频

Imaging Studies I: Kidney, Ureter, and Bladder Studies01:28

Imaging Studies I: Kidney, Ureter, and Bladder Studies

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Kidney, Ureter, and Bladder (KUB) StudiesKidney, Ureter, and Bladder (KUB) studies are standard diagnostic imaging procedures used to assess the anatomy of the urinary system. They are commonly utilized for patients experiencing abdominal pain or urinary symptoms. By using a simple X-ray of the abdomen, KUB studies can reveal structural and pathological abnormalities within the kidneys, ureters, and bladder. These studies are particularly valuable in diagnosing kidney stones, urinary...
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Classification of Illness01:17

Classification of Illness

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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Chronic Kidney Disease II: Clinical Manifestations01:24

Chronic Kidney Disease II: Clinical Manifestations

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Chronic Kidney Disease (CKD) progressively impairs multiple body systems due to the accumulation of uremic toxins, which disrupt cellular functions across various organs.Neurologic symptomsNeurologic symptoms often arise early in CKD, as uremic toxin buildup drives changes in cognitive and motor functions. Patients frequently experience fatigue, headache, confusion, difficulty concentrating, and, in severe cases, seizures. Peripheral neuropathy commonly manifests as burning sensations in the...
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Chronic Kidney Disease I: Introduction01:25

Chronic Kidney Disease I: Introduction

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Chronic Kidney Disease (CKD) arises when the kidneys progressively lose their ability to function, ultimately leading to end-stage renal disease. At this advanced stage, the kidneys can no longer filter waste or maintain essential body functions, requiring renal replacement therapy (RRT) through dialysis or a kidney transplant for survival.Early-stage chronic kidney disease and detection challengesIn CKD's early stages, symptoms often remain absent because healthy nephrons compensate for...
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Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

Acute Kidney Injury IV: Diagnostic Studies and Prevention

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Accurate diagnosis and effective prevention are critical in managing Acute Kidney Injury (AKI), which is linked to high mortality rates ranging from 10% to 80%. Timely recognition of at-risk patients and careful monitoring can significantly reduce the likelihood of kidney damage.Diagnostic Assessments:The diagnostic process starts with a comprehensive medical history to identify prerenal, intrarenal, and postrenal causes.Prerenal causes, such as dehydration, hypotension, or blood loss, should...
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External Anatomy of the Kidney01:21

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The kidneys are a pair of bean-shaped organs in the human body that play a critical role in maintaining overall health. They filter out waste products from the blood, regulate blood pressure, maintain electrolyte balance, and stimulate the production of red blood cells.
The kidneys are located in the retroperitoneal space on either side of the vertebral column, protected posteriorly by the 11th and 12th ribs. The right kidney sits slightly lower than the left owing to the presence of the liver...
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    科学领域:

    • 脏病理学 脏病理学
    • 计算病理学计算病理学
    • 医学中的人工智能.

    背景情况:

    • 活检的组织学分析对于诊断脏疾病和预测结果至关重要.
    • 在大型数据集上预训练的病理学基础模型,为下游任务提供了有希望的性能.
    • 将这些模型与多个实例学习 (MIL) 集成为病理学分析,需要进行调查.

    研究的目的:

    • 评估病理学基础模型与MIL结合用于病理学分析的实用性.
    • 将基础模型的诊断性能与传统的ResNet50模型进行比较.
    • 评估模型对外部数据集进行概括和预测临床结果的能力.

    主要方法:

    • 从KPMP和JP-AID中使用了242个H&E染色完整幻灯片图像 (WSI) 来进行内部验证.
    • 包括健康对照组,急性间歇性炎和糖尿病病 (DKD) 病例.
    • 执行了来自东京大学医院 (UT数据集) 的83个WSI的外部验证.
    • 采用预训练的病理基础模型作为补丁编码器,将其与ImageNet预训练的ResNet50.0进行比较.

    主要成果:

    • 基础模型在内部验证中显著优于ResNet50 (AUROC>0.980).
    • 在外部验证中,基础模型保持了高性能 (AUROC > 0.800),而ResNet50的性能下降了 (AUROC = 0.768).
    • 注意热图证实了基础模型,识别了诊断相关的结构.
    • 基础模型在预测DKD病例中严重蛋白尿症方面也超过了ResNet50.

    结论:

    • 与MIL集成的病理学基础模型在病理学中实现了强大的诊断性能.
    • 这些模型表现出强大的概括能力,即使训练数据有限.
    • 这些发现突出了基础模型在病诊断中对现实世界的临床应用的潜力.