AIMC Topic: Humans

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Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation.

IEEE transactions on medical imaging
Anatomical abnormality detection and report generation of chest X-ray (CXR) are two essential tasks in clinical practice. The former aims at localizing and characterizing cardiopulmonary radiological findings in CXRs, while the latter summarizes the ...

HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization.

IEEE transactions on medical imaging
Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studies attempt to adopt the class activation map (CAM), a weakly-supervised...

MT-CooL: Multi-Task Cooperative Learning via Flat Minima Searching.

IEEE transactions on medical imaging
While multi-task learning (MTL) has been widely developed for natural image analysis, its potential for enhancing performance in medical imaging remains relatively unexplored. Most methods formulate MTL as a multi-objective problem, inherently forcin...

POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation.

IEEE transactions on medical imaging
Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging. However, the prevalent practice of employing additional CT scans for generating attenuation maps ( -map) for PET attenuation correction significantly elevates radia...

Using artificial intelligence tools to automate data extraction for living evidence syntheses.

PloS one
Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article sea...

Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model.

PloS one
Enterprise risk management is a key element to ensure the sustainable and steady development of enterprises. However, traditional risk management methods have certain limitations when facing complex market environments and diverse risk events. This s...

Positive relationship between education level and risk perception and behavioral response: A machine learning approach.

PloS one
This paper aims to examine the influence mechanism of education level as a key situational factor in the relationship between risk perception and behavioral response, encompassing both behavioral intention and preparatory behavior. Utilizing non-para...

Adaptive Dual-Axis Style-Based Recalibration Network With Class-Wise Statistics Loss for Imbalanced Medical Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Salient and small lesions (e.g., microaneurysms on fundus) both play significant roles in real-world disease diagnosis under medical image examinations. Although deep neural networks (DNNs) have achieved promising medical image classification perform...

AI-enabled AT Framework: a principles-based approach to emerging assistive technology.

Disability and rehabilitation. Assistive technology
Assistive Technology (AT) is an umbrella term that describes the combination of devices and services used by individuals with a disability to perform tasks that might otherwise be difficult or impossible to complete due to their disability. Increasi...

Sulforaphane protects developing neural networks from VPA-induced synaptic alterations.

Molecular psychiatry
Prenatal brain development is particularly sensitive to chemicals that can disrupt synapse formation and cause neurodevelopmental disorders. In most cases, such chemicals increase cellular oxidative stress. For example, prenatal exposure to the anti-...