AIMC Topic: Algorithms

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Raw data consistent deep learning-based field of view extension for dual-source dual-energy CT.

Medical physics
BACKGROUND: Due to technical constraints, dual-source dual-energy CT scans may lack spectral information in the periphery of the patient.

Self-orienting in human and machine learning.

Nature human behaviour
A current proposal for a computational notion of self is a representation of one's body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientatio...

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15.

Proteins
We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure pred...

Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology.

AJNR. American journal of neuroradiology
In this review, concepts of algorithmic bias and fairness are defined qualitatively and mathematically. Illustrative examples are given of what can go wrong when unintended bias or unfairness in algorithmic development occurs. The importance of expla...

Marker-Free Isoelectric Focusing Patterns for Identification of Meat Samples via Deep Learning.

Analytical chemistry
Isoelectric focusing (IEF) is a powerful tool for resolving complex protein samples, which generates IEF patterns consisting of multiplex analyte bands. However, the interpretation of IEF patterns requires the careful selection of isoelectric point (...

Fundus Image-Label Pairs Synthesis and Retinopathy Screening via GANs With Class-Imbalanced Semi-Supervised Learning.

IEEE transactions on medical imaging
Retinopathy is the primary cause of irreversible yet preventable blindness. Numerous deep-learning algorithms have been developed for automatic retinal fundus image analysis. However, existing methods are usually data-driven, which rarely consider th...

Low-Dose CT Image Synthesis for Domain Adaptation Imaging Using a Generative Adversarial Network With Noise Encoding Transfer Learning.

IEEE transactions on medical imaging
Deep learning (DL) based image processing methods have been successfully applied to low-dose x-ray images based on the assumption that the feature distribution of the training data is consistent with that of the test data. However, low-dose computed ...

Application of artificial neural network in daily prediction of bleeding in ICU patients treated with anti-thrombotic therapy.

BMC medical informatics and decision making
OBJECTIVES: Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is the main adverse event of anti-thrombosis. Existing laboratory indicators cannot accurately reflect the real-time coagulation function. It is necessa...

Identification of growth years for Puerariae Thomsonii Radix based on hyperspectral imaging technology and deep learning algorithm.

Scientific reports
Puerariae Thomsonii Radix (PTR) is not only widely used in disease prevention and treatment but is also an important raw material as a source of starch and other food. The growth years of PTR are closely related to its quality. The rapid and nondestr...

A synthetic data generation system for myalgic encephalomyelitis/chronic fatigue syndrome questionnaires.

Scientific reports
Artificial intelligence or machine-learning-based models have proven useful for better understanding various diseases in all areas of health science. Myalgic Encephalomyelitis or chronic fatigue syndrome (ME/CFS) lacks objective diagnostic tests. Som...