AIMC Topic: Humans

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The Practical, Robust Implementation and Sustainability (PRISM)-capabilities model for use of Artificial Intelligence in community-engaged implementation science research.

Implementation science : IS
BACKGROUND: Community-engaged research (CER) leverages knowledge, insights, and expertise of researchers and communities to address complex public health challenges and improve community well-being. CER fosters collaboration throughout all research p...

Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.

BMC health services research
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...

Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

BMC medical informatics and decision making
BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments. Reduced facial expressions are considered a hallmark of PD, making advanced artificial intelligence (AI) image processing a potential non-invasive c...

Identification and experimental validation of mitochondrial and endoplasmic reticulum stress related gene in diabetic nephropathy.

Scientific reports
Diabetic nephropathy (DN) is a kidney disease. Mitochondrial and endoplasmic reticulum stress (ERS) significantly contribute to diabetic nephropathy (DN), although the precise mechanisms involved have not yet been fully understood. The objective of t...

Urinary Complement proteome strongly linked to diabetic kidney disease progression.

Nature communications
Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...

Explainable illicit drug abuse prediction using hematological differences.

Scientific reports
This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDU...

A Comprehensive Behavioral Dataset for the Abstraction and Reasoning Corpus.

Scientific data
The Abstraction and Reasoning Corpus (ARC) is a visual program synthesis benchmark designed to test out-of-distribution generalization in machines. Comparing AI algorithms to human performance is essential to measure progress on these problems. In th...

CAS-Colon: A Comprehensive Colonoscopy Anatomical Segmentation Dataset for Artificial Intelligence Development.

Scientific data
Artificial intelligence (AI) holds immense potential to transform gastrointestinal endoscopy by reducing manual workload and enhancing procedural efficiency. However, the development of robust AI algorithms is hindered by limited access to high-quali...

Proactive care architecture for care robots.

Scientific reports
Care robots have been developed to address the shortage of human caregivers in aging societies facing declining birth rates. However, currently care robots only passively perform care tasks based on commands, they are unable to provide care services ...

Quantitative image analysis of the extracellular matrix of esophageal squamous cell carcinoma and high grade dysplasia via two-photon microscopy.

Scientific reports
Squamous cell carcinoma (SCC) and high-grade dysplasia (HGD) are two different pathological entities; however, they sometimes share similarities in histological structure depending on the context. Thus, distinguishing between the two may require care...