AIMC Topic: Humans

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Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...

Flexor Synergy Assessment and Therapy for Persons With Stroke Using the ULIX Low Impedance Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The flexor synergy after stroke results in involuntary activation of distal muscles when lifting the shoulder against gravity. This contributes to impaired ability to perform activities of daily living. Robotic exoskeletons can be useful in assessing...

SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...

Contouring in transition: perceptions of AI-based autocontouring by radiation oncologists and medical physicists in German-speaking countries.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: Artificial intelligence (AI)-based autocontouring software has the potential to revolutionize radiotherapy planning. In recent years, several AI-based autocontouring solutions with many advantages have emerged; however, their clinical use...

Methodology for a fully automated pipeline of AI-based body composition tools for abdominal CT.

Abdominal radiology (New York)
Accurate, reproducible body composition analysis from abdominal computed tomography (CT) images is critical for both clinical research and patient care. We present a fully automated, artificial intelligence (AI)-based pipeline that streamlines the en...

State of the art review of AI in renal imaging.

Abdominal radiology (New York)
Renal cell carcinoma (RCC) as a significant health concern, with incidence rates rising annually due to increased use of cross-sectional imaging, leading to a higher detection of incidental renal lesions. Differentiation between benign and malignant ...

"I don't know": An uncertainty-aware machine learning model for predicting patient disposition at emergency department triage.

International journal of medical informatics
BACKGROUND: Machine learning (ML) models are widely used for predicting patient disposition at emergency department (ED) triage. However, these models generate predictions regardless of the level of uncertainty, potentially leading to overconfident o...

Risk calculator for long-term survival prediction of spinal chordoma versus chondrosarcoma: a nationwide analysis.

Journal of neuro-oncology
PURPOSE: Chordomas and chondrosarcomas are rare, aggressive spinal bone tumors with distinct origins, biological behavior, and treatment challenges, primarily due to their resistance to conventional chemotherapy and radiation. This study aimed to com...

Evaluating the novel role of ChatGPT-4 in addressing corneal ulcer queries: An AI-powered insight.

European journal of ophthalmology
PurposeChatGPT-4, a natural language processing-based AI model, is increasingly being applied in healthcare, facilitating education, research, and clinical decision-making support. This study explores ChatGPT-4's capability to deliver accurate and de...

VTrans: A VAE-Based Pre-Trained Transformer Method for Microbiome Data Analysis.

Journal of computational biology : a journal of computational molecular cell biology
Predicting the survival outcomes and assessing the risk of patients play a pivotal role in comprehending the microbial composition across various stages of cancer. With the ongoing advancements in deep learning, it has been substantiated that deep le...