AIMC Topic: Humans

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An integrative machine learning model for the identification of tumor T-cell antigens.

Bio Systems
The escalating global incidence of cancer poses significant health challenges, underscoring the need for innovative and more efficacious treatments. Cancer immunotherapy, a promising approach leveraging the body's immune system against cancer, emerge...

A scoping review of fair machine learning techniques when using real-world data.

Journal of biomedical informatics
OBJECTIVE: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fair...

Artificial intelligence and illusions of understanding in scientific research.

Nature
Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of ...

A Physics-Informed Low-Shot Adversarial Learning for sEMG-Based Estimation of Muscle Force and Joint Kinematics.

IEEE journal of biomedical and health informatics
Muscle force and joint kinematics estimation from surface electromyography (sEMG) are essential for real-time biomechanical analysis of the dynamic interplay among neural muscle stimulation, muscle dynamics, and kinetics. Recent advances in deep neur...

Quaternion Cross-Modality Spatial Learning for Multi-Modal Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Recently, the Deep Neural Networks (DNNs) have had a large impact on imaging process including medical image segmentation, and the real-valued convolution of DNN has been extensively utilized in multi-modal medical image segmentation to accurately se...

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records.

IEEE journal of biomedical and health informatics
Text classification is a central part of natural language processing, with important applications in understanding the knowledge behind biomedical texts including electronic health records (EHR). In this article, we propose a novel heterogeneous grap...

A New Multi-Atlas Based Deep Learning Segmentation Framework With Differentiable Atlas Feature Warping.

IEEE journal of biomedical and health informatics
Deep learning based multi-atlas segmentation (DL-MA) has achieved the state-of-the-art performance in many medical image segmentation tasks, e.g., brain parcellation. In DL-MA methods, atlas-target correspondence is the key for accurate segmentation....

Contactless Respiration Monitoring Using Wi-Fi and Artificial Neural Network Detection Method.

IEEE journal of biomedical and health informatics
Detecting respiration in a non-intrusive manner is beneficial not only for convenience but also for cases where the traditional ways cannot be applied. This paper presents a novel simple low-cost system where ambient Wi-Fi signals are acquired by a t...

Human Locomotion Databases: A Systematic Review.

IEEE journal of biomedical and health informatics
The analysis of human locomotion is highly dependent on the quantity and quality of available data to obtain reliable evidence, due to the great variability of gait characteristics between subjects. Researchers usually have to make significant effort...

NERONE: The Fast Way to Efficiently Execute Your Deep Learning Algorithm at the Edge.

IEEE journal of biomedical and health informatics
Semantic segmentation and classification are pivotal in many clinical applications, such as radiation dose quantification and surgery planning. While manually labeling images is highly time-consuming, the advent of Deep Learning (DL) has introduced a...