AIMC Topic: Humans

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Event-driven figure-ground organisation model for the humanoid robot iCub.

Nature communications
Figure-ground organisation is a perceptual grouping mechanism for detecting objects and boundaries, essential for an agent interacting with the environment. Current figure-ground segmentation methods rely on classical computer vision or deep learning...

AI-augmented Biophysical modeling in thermoplasmonics for real-time monitoring and diagnosis of human tissue infections.

Journal of thermal biology
Identifying tissue infections from the body still poses an unprecedented challenge in society. Conventional diagnostic procedures are time-consuming and lack a real-time monitoring mode. This study proposes a system with an Artificial Intelligence (A...

Optimizing thermal dose prediction in nanoparticle-mediated photothermal therapy using a convolutional neural network-based model.

Journal of thermal biology
Nanoparticle-mediated photothermal therapy (NMPTT) is an up-and-coming targeted cancer treatment. Here, nanoparticles are used to convert near-infrared light into localized heat that can kill tumour cells while sparing surrounding healthy tissue. Nev...

Biophysical versus machine learning models for predicting rectal and skin temperatures in older adults.

Journal of thermal biology
This study compares the efficacy of machine learning models to traditional biophysical models in predicting rectal (T) and skin (T) temperatures of older adults (≥60 years) during prolonged heat exposure. Five machine learning models were trained on ...

Advanced echocardiography and cluster analysis to identify secondary tricuspid regurgitation phenogroups at different risk.

Revista espanola de cardiologia (English ed.)
INTRODUCTION AND OBJECTIVES: Significant secondary tricuspid regurgitation (STR) is associated with poor prognosis, but its heterogeneity makes predicting patient outcomes challenging. Our objective was to identify STR prognostic phenogroups.

NPI-HGNN: A Heterogeneous Graph Neural Network-Based Approach for Predicting ncRNA-Protein Interactions.

Interdisciplinary sciences, computational life sciences
Accurate identification of ncRNA-protein interactions (NPIs) is critical for understanding various cellular activities and biological functions of ncRNAs and proteins. Many sequence- and/or structure- and graph-based computational approaches have bee...

Current State of Evidence for Use of MRI in LI-RADS.

Journal of magnetic resonance imaging : JMRI
The American College of Radiology Liver Imaging Reporting and Data System (LI-RADS) is the preeminent framework for classification and risk stratification of liver observations on imaging in patients at high risk for hepatocellular carcinoma. In this...

Raman spectroscopy for colorectal tumor margin assessment: A promising tool for real-time surgical delimitation.

Talanta
Raman spectroscopy is a promising non-invasive technique not only for the rapid and accurate detection of colorectal cancer (CRC) but also for the identification of positive surgical margins. In this study, micro-Raman spectroscopy was used to explor...

Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis.

Molecular diversity
The viability of cells and the integrity of the genome depend on the detection and repair of damaged DNA through intricate mechanisms. Cancer treatment employs chemotherapy or radiation therapy to eliminate neoplastic cells by causing substantial dam...