AIMC Topic: Humans

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Lesion attention guided neural network for contrast-enhanced mammography-based biomarker status prediction in breast cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate identification of molecular biomarker statuses is crucial in cancer diagnosis, treatment, and prognosis. Studies have demonstrated that medical images could be utilized for non-invasive prediction of biomarker statu...

Advancing musculoskeletal tumor diagnosis: Automated segmentation and predictive classification using deep learning and radiomics.

Computers in biology and medicine
OBJECTIVES: Musculoskeletal (MSK) tumors, given their high mortality rate and heterogeneity, necessitate precise examination and diagnosis to guide clinical treatment effectively. Magnetic resonance imaging (MRI) is pivotal in detecting MSK tumors, a...

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles.

Computers in biology and medicine
Distant metastasis of cancer is a significant contributor to cancer-related complications, and early identification of unidentified stomach adenocarcinoma is crucial for a positive prognosis. Changes inDNA methylation are being increasingly recognize...

RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic registration of differently stained whole slide images (WSIs) is crucial for improving diagnosis and prognosis by fusing complementary information emerging from different visible structures. It is also useful t...

How robot-assisted gait training affects gait ability, balance and kinematic parameters after stroke: a systematic review and meta-analysis.

European journal of physical and rehabilitation medicine
INTRODUCTION: Gait ability is often cited by stroke survivors. Robot-assisted gait training (RAGT) can help stroke patients with lower limb motor impairment regain motor coordination.

A Soft Collaborative Robot for Contact-based Intuitive Human Drag Teaching.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Soft material-based robots, known for their safety and compliance, are expected to play an irreplaceable role in human-robot collaboration. However, this expectation is far from real industrial applications due to their complex programmability and po...

A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).

Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...

Physics-Informed Transfer Learning to Enhance Sleep Staging.

IEEE transactions on bio-medical engineering
OBJECTIVE: At-home sleep staging using wearable medical sensors poses a viable alternative to in-hospital polysomnography due to its lower cost and lower disruption to the daily lives of patients, especially in the case of long-term monitoring. Machi...

Frequency Domain Channel-Wise Attack to CNN Classifiers in Motor Imagery Brain-Computer Interfaces.

IEEE transactions on bio-medical engineering
OBJECTIVE: Convolutional neural network (CNN), a classical structure in deep learning, has been commonly deployed in the motor imagery brain-computer interface (MIBCI). Many methods have been proposed to evaluate the vulnerability of such CNN models,...