AIMC Topic: Adult

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Shared Control of Supernumerary Robotic Limbs Using Mixed Realityand Mouth-and-Tongue Interfaces.

Biosensors
Supernumerary Robotic Limbs (SRLs) are designed to collaborate with the wearer, enhancing operational capabilities. When human limbs are occupied with primary tasks, controlling SRLs flexibly and naturally becomes a challenge. Existing methods such a...

Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Intensive rehabilitation through challenging and individualized tasks are recommended to enhance upper limb recovery after stroke. Robot-assisted therapy (RAT) and serious games could be used to enhance functional recovery by providing si...

Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score.

BMC emergency medicine
BACKGROUND: Traumatic injuries are a leading cause of morbidity and mortality globally, with a disproportionate impact on populations in low- and middle-income countries (LMICs). The Kampala Trauma Score (KTS) is frequently used for triage in these s...

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study.

JMIR research protocols
BACKGROUND: Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective...

The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis.

Frontiers in immunology
BACKGROUND: Severe Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the role of biomarkers such as Connective Tissue Growth Factor (CTGF) and Milk Fat Globule-Epidermal Gro...

What factors influence the willingness and intensity of regular mobile physical activity?- A machine learning analysis based on a sample of 290 cities in China.

Frontiers in public health
INTRODUCTION: This study, based on Volunteered Geographic Information (VGI) and multi-source data, aims to construct an interpretable macro-scale analytical framework to explore the factors influencing urban physical activities. Using 290 prefecture-...

CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.

Abdominal radiology (New York)
BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced ...

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.

Abdominal radiology (New York)
PURPOSE: Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI.

Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.

European radiology
OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.