AIMC Topic: Aged, 80 and over
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Diagnostic Performance of Different Examination Types and Learning Curves of Radiologists for 5G-Based Robot-Assisted Tele-Ultrasonography: A Prospective and Large-Scale Study.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jan 22, 2025
OBJECTIVE: To investigate the feasibility of remotely providing routine ultrasound (US) examinations to patients using a fifth-generation-based robot-assisted tele-ultrasonography (RATU) system in a real-world setting.
"Tom and Pepper Lab". Robotics for cognitive stimulation and social skills: A preliminary study.
Asian journal of psychiatry
Jan 22, 2025
Dementia affects over 55 million people globally, with early cognitive decline, such as Mild Cognitive Impairment (MCI), often preceding neurodegenerative diseases. This decline impairs memory, attention, and Theory of Mind (ToM). Early intervention ...
Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study.
BMC cancer
Jan 22, 2025
BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitat...
Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography.
EBioMedicine
Jan 21, 2025
BACKGROUND: Transthoracic echocardiography (TTE) is the primary modality for diagnosing aortic stenosis (AS), yet it requires skilled operators and can be resource-intensive. We developed and validated an artificial intelligence (AI)-based system for...
AI Machine Learning-Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis.
JMIR formative research
Jan 21, 2025
BACKGROUND: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.
Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.
Alzheimer's research & therapy
Jan 21, 2025
BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatme...
Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia.
Translational psychiatry
Jan 21, 2025
Existing dementia prediction models using non-neuroimaging clinical measures have been limited in their ability to identify disease. This study used machine learning to re-examine the diagnostic potential of clinical measures for dementia. Data was s...
Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.
Circulation. Cardiovascular imaging
Jan 21, 2025
BACKGROUND: Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricusp...
Constructing a fall risk prediction model for hospitalized patients using machine learning.
BMC public health
Jan 20, 2025
STUDY OBJECTIVES: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.
Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy.
Scientific reports
Jan 20, 2025
This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and to evaluate the diagnostic power of Raman spectroscopy-based machine learning in gastric adenocarcin...
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