AIMC Topic: Humans

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Automated Single Cell Phenotyping of Time-of-Flight Secondary Ion Mass Spectrometry Tissue Images.

Journal of the American Society for Mass Spectrometry
Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many diffe...

Uncovering global risk to human and ecosystem health from pesticides in agricultural surface water using a machine learning approach.

Environment international
Pesticides typically co-occur in agricultural surface waters and pose a potential threat to human and ecosystem health. As pesticide screening in global agricultural surface waters is an immense analytical challenge, a detailed risk picture of pestic...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on brain magnetic resonance imaging (MRI) is significant in assisting the diagnosis of PD. However, due to the degenerative-induced changes in appearance, ...

CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases. Accurate 3D segmentation of the aorta and its branches is crucial for interventions, as inaccurate segmentation can lead to ...

Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder.

Journal of biomedical informatics
Cancer is a disease that causes many deaths worldwide. The treatment of cancer is first and foremost a matter of detection, a treatment that is most effective when the disease is detected at an early stage. With the evolution of technology, several c...

Targeting mitochondria in Cancer therapy: Machine learning analysis of hyaluronic acid-based drug delivery systems.

International journal of biological macromolecules
BACKGROUND: Mitochondrial alterations play a crucial role in the development and progression of cancer. Dysfunctional mitochondria contribute to the acquisition of key hallmarks of cancer, including sustained proliferative signaling, evasion of growt...

Using ChatGPT in Nursing: Scoping Review of Current Opinions.

JMIR medical education
BACKGROUND: Since the release of ChatGPT in November 2022, this emerging technology has garnered a lot of attention in various fields, and nursing is no exception. However, to date, no study has comprehensively summarized the status and opinions of u...

A Novel and Powerful Dual-Stream Multi-Level Graph Convolution Network for Emotion Recognition.

Sensors (Basel, Switzerland)
Emotion recognition enables machines to more acutely perceive and understand users' emotional states, thereby offering more personalized and natural interactive experiences. Given the regularity of the responses of brain activity to human cognitive p...

AI-Aided Gait Analysis with a Wearable Device Featuring a Hydrogel Sensor.

Sensors (Basel, Switzerland)
Wearable devices have revolutionized real-time health monitoring, yet challenges persist in enhancing their flexibility, weight, and accuracy. This paper presents the development of a wearable device employing a conductive polyacrylamide-lithium chlo...

Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.

International journal of molecular sciences
In oncology, there is a critical need for robust biomarkers that can be easily translated into the clinic. We introduce a novel approach using paired differential gene expression analysis for biological feature selection in machine learning models, e...