AIMC Topic: Algorithms

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A Generative Model to Synthesize EEG Data for Epileptic Seizure Prediction.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
OBJECTIVE: Scarcity of good quality electroencephalography (EEG) data is one of the roadblocks for accurate seizure prediction. This work proposes a deep convolutional generative adversarial network (DCGAN) to generate synthetic EEG data. Another obj...

Parallel multi-fusion convolutional neural networks based fault diagnosis of rotating machinery under noisy environments.

ISA transactions
Fault diagnosis has a great significance in preventing serious failures of rotating machinery and avoiding huge economic losses. The performance of the existing fault diagnosis approaches might be affected by two factors, i.e., the quality of fault f...

Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

British journal of anaesthesia
BACKGROUND: Artificial intelligence (AI) has the potential to personalise mechanical ventilation strategies for patients with respiratory failure. However, current methodological deficiencies could limit clinical impact. We identified common limitati...

Machine intelligence in non-invasive endocrine cancer diagnostics.

Nature reviews. Endocrinology
Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care system replete with enhanced precision and computing capabilities. Medical imaging analysis can be strengthened by machine learning as the multidimensional data...

LF-ACO: an effective formation path planning for multi-mobile robot.

Mathematical biosciences and engineering : MBE
Multi-robot path planning is a hot problem in the field of robotics. Compared with single-robot path planning, complex problems such as obstacle avoidance and mutual collaboration need to be considered. This paper proposes an efficient leader followe...

Survival prediction among heart patients using machine learning techniques.

Mathematical biosciences and engineering : MBE
Cardiovascular diseases are regarded as the most common reason for worldwide deaths. As per World Health Organization, nearly 17.9 million people die of heart-related diseases each year. The high shares of cardiovascular-related diseases in total wor...

Towards Autonomous Drone Racing without GPU Using an OAK-D Smart Camera.

Sensors (Basel, Switzerland)
Recent advances have shown for the first time that it is possible to beat a human with an autonomous drone in a drone race. However, this solution relies heavily on external sensors, specifically on the use of a motion capture system. Thus, a truly a...

Machine Learning-Based Prediction of Drug-Drug Interactions for Histamine Antagonist Using Hybrid Chemical Features.

Cells
The requesting of detailed information on new drugs including drug-drug interactions or targets is often unavailable and resource-intensive in assessing adverse drug events. To shorten the common evaluation process of drug-drug interactions, we prese...

A robust and stable gene selection algorithm based on graph theory and machine learning.

Human genomics
BACKGROUND: Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data i...

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BMC medical informatics and decision making
BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is not feasible using only structured data but requires labor-intensive chart review of electronic heal...