AIMC Topic: Algorithms

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AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors.

Journal of biomolecular structure & dynamics
Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate cancer (PCa). AR controls the transcription of genes that help cells avoid apoptosis and proliferate, thereby contributing to the development of PCa. Und...

Data-driven crash prediction by injury severity using a recurrent neural network model based on Keras framework.

International journal of injury control and safety promotion
With the development of big data technology and the improvement of deep learning technology, data-driven and machine learning application have been widely employed. By adopting the data-driven machine learning method, with the help of clustering proc...

ATNAS: Automatic Termination for Neural Architecture Search.

Neural networks : the official journal of the International Neural Network Society
Neural architecture search (NAS) is a framework for automating the design process of a neural network structure. While the recent one-shot approaches have reduced the search cost, there still exists an inherent trade-off between cost and performance....

CO-WOA: Novel Optimization Approach for Deep Learning Classification of Fish Image.

Chemistry & biodiversity
The most significant groupings of cold-blooded creatures are the fish family. It is crucial to recognize and categorize the most significant species of fish since various species of seafood diseases and decay exhibit different symptoms. Systems based...

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization.

Sensors (Basel, Switzerland)
Optical coherence tomography (OCT) is widely used to detect and classify retinal diseases. However, OCT-image-based manual detection by ophthalmologists is prone to errors and subjectivity. Thus, various automation methods have been proposed; however...

Mud Ring Optimization Algorithm with Deep Learning Model for Disease Diagnosis on ECG Monitoring System.

Sensors (Basel, Switzerland)
Due to the tremendous growth of the Internet of Things (IoT), sensing technologies, and wearables, the quality of medical services has been enhanced, and it has shifted from standard medical-based health services to real time. Commonly, the sensors c...

Hybrid convolution neural network with channel attention mechanism for sensor-based human activity recognition.

Scientific reports
In the field of machine intelligence and ubiquitous computing, there has been a growing interest in human activity recognition using wearable sensors. Over the past few decades, researchers have extensively explored learning-based methods to develop ...

Dynamic robotic tracking of underwater targets using reinforcement learning.

Science robotics
To realize the potential of autonomous underwater robots that scale up our observational capacity in the ocean, new techniques are needed. Fleets of autonomous robots could be used to study complex marine systems and animals with either new imaging c...

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumptio...

Data-driven decisions about individual patients: The case of medical AI.

Journal of evaluation in clinical practice
There are high hopes that clinical decisions can be improved by adopting algorithms trained to estimate the likelihood that a patient suffers a condition C. Introducing work on the epistemic value of purely statistical evidence in legal epistemology ...