AIMC Topic: Humans

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A Survey on Brain Effective Connectivity Network Learning.

IEEE transactions on neural networks and learning systems
Human brain effective connectivity characterizes the causal effects of neural activities among different brain regions. Studies of brain effective connectivity networks (ECNs) for different populations contribute significantly to the understanding of...

High-resolution rural poverty mapping in Pakistan with ensemble deep learning.

PloS one
High resolution poverty mapping supports evidence-based policy and research, yet about half of all countries lack the survey data needed to generate useful poverty maps. To overcome this challenge, new non-traditional data sources and deep learning t...

BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images.

PloS one
Breast cancer is the most common malignancy in women, with over 40,000 deaths annually in the United States alone. Clinicians often rely on the breast cancer recurrence score, Oncotype DX (ODX), for risk stratification of breast cancer patients, by u...

Remote assessment of cognition and quality of life following radiotherapy for nasopharyngeal carcinoma: deep-learning-based predictive models and MRI correlates.

Journal of cancer survivorship : research and practice
PURPOSE: Irradiation of the brain regions from nasopharyngeal carcinoma (NPC) radiotherapy (RT) is frequently unavoidable, which may result in radiation-induced cognitive deficit. Using deep learning (DL), the study aims to develop prediction models ...

Characterization of noise in long-term ECG monitoring with machine learning based on clinical criteria.

Medical & biological engineering & computing
Noise and artifacts affect strongly the quality of the electrocardiogram (ECG) in long-term ECG monitoring (LTM), making some of its parts impractical for diagnosis. The clinical severity of noise defines a qualitative quality score according to the ...

Application of the Xi robotic platform for familial adenomatous polyposis with ultra-low rectal cancer: exploration of minimally invasive and refined therapies.

Journal of robotic surgery
When a familial adenomatous polyposis (FAP) patient's rectal polyp undergoes malignant transformation, the surgeon needs to consider how to balance the quality of surgery with the patient's quality of life. Here, we present a case of robotic surgery ...

Pushing the limits of low-cost ultra-low-field MRI by dual-acquisition deep learning 3D superresolution.

Magnetic resonance in medicine
PURPOSE: Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shielding-free, and portable clinical applications at a fraction of the cost. However, its performance remains limited by poor image quality. Here, a compu...

Synthetic CT generation from CBCT using double-chain-CycleGAN.

Computers in biology and medicine
PURPOSE: Cone-beam CT (CBCT) has the advantage of being less expensive, lower radiation dose, less harm to patients, and higher spatial resolution. However, noticeable noise and defects, such as bone and metal artifacts, limit its clinical applicatio...

An attention-based deep convolutional neural network for ultra-sparse-view CT reconstruction.

Computers in biology and medicine
X-ray Computed Tomography (CT) techniques play a vitally important role in clinical diagnosis, but radioactivity exposure can also induce the risk of cancer for patients. Sparse-view CT reduces the impact of radioactivity on the human body through sp...