AIMC Topic: Aged

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Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Reticular pseudodrusen (RPD), a key feature of age-related macular degeneration (AMD), are poorly detected by human experts on standard color fundus photography (CFP) and typically require advanced imaging modalities such as fundus autoflu...

Improving the delivery of palliative care through predictive modeling and healthcare informatics.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address...

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patien...

Automated model versus treating physician for predicting survival time of patients with metastatic cancer.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Being able to predict a patient's life expectancy can help doctors and patients prioritize treatments and supportive care. For predicting life expectancy, physicians have been shown to outperform traditional models that use only a few pred...

Predicting ventilator-associated pneumonia with machine learning.

Medicine
Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifying VAP display low accuracy, and their use may delay antimicrobial therapy. VAP diagnostics derived ...

T-able: An Investigation of Habituating Moving Tables at Home.

Studies in health technology and informatics
This paper investigates the philosophical and designerly questions of how the concepts of familiarity, orientation, and habituation can be used to understand a self-moving (semi-autonomous robot) table at home. Tables are familiar habituated objects ...

Categorising patient concerns using natural language processing techniques.

BMJ health & care informatics
OBJECTIVES: Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the result...

[Robot-assisted nephroureterectomy requiring no robot redocking or patient repositioning: experience from a single center with 62 cases].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine a new technique of robot-assisted nephroureterectomy without robot reldocking or patient repositioning. Patients diagnosed as upper tract urothelial carcinoma treated with this modality between November 2015 and January 2019 at Departmen...

Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction.

JAMA cardiology
IMPORTANCE: Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making, and novel methods hold promise for using existing data to generate additional insights.

A Deep-Learning-Based, Fully Automated Program to Segment and Quantify Major Spinal Components on Axial Lumbar Spine Magnetic Resonance Images.

Physical therapy
OBJECTIVE: The paraspinal muscles have been extensively studied on axial lumbar magnetic resonance imaging (MRI) for better understanding of back pain; however, the acquisition of measurements mainly relies on manual segmentation, which is time consu...