AIMC Topic: Algorithms

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Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Early unplanned hospital readmissions are associated with increased harm to patients, increased medical costs, and negative hospital reputation. With the identification of at-risk patients, a crucial step toward improving care, appropriat...

Fast activation maximization for molecular sequence design.

BMC bioinformatics
BACKGROUND: Optimization of DNA and protein sequences based on Machine Learning models is becoming a powerful tool for molecular design. Activation maximization offers a simple design strategy for differentiable models: one-hot coded sequences are fi...

Model Construction of Using Physiological Signals to Detect Mental Health Status.

Journal of healthcare engineering
BACKGROUND: Mental health is a direct indicator of human mental activity, and it also affects all aspects of the human body. It plays a very important role in monitoring human mental health.

Tumor Region Location and Classification Based on Fuzzy Logic and Region Merging Image Segmentation Algorithm.

Journal of healthcare engineering
Early diagnosis of tumor plays an important role in the improvement of treatment and survival rate of patients. However, breast tumors are difficult to be diagnosed by invasive examination, so medical imaging has become the most intuitive auxiliary m...

Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study.

EBioMedicine
BACKGROUND: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images.

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

IEEE transactions on bio-medical engineering
OBJECTIVES: Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used sup...

HARNAS: Human Activity Recognition Based on Automatic Neural Architecture Search Using Evolutionary Algorithms.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) based on wearable sensors is a promising research direction. The resources of handheld terminals and wearable devices limit the performance of recognition and require lightweight architectures. With the development of...

Noninvasive Methods for Fault Detection and Isolation in Internal Combustion Engines Based on Chaos Analysis.

Sensors (Basel, Switzerland)
The classic monitoring methods for detecting faults in automotive vehicles based on on-board diagnostics (OBD) are insufficient when diagnosing several mechanical failures. Other sensing techniques present drawbacks such as high invasiveness and limi...

Novel Prediction of Diagnosis Effectiveness for Adaptation of the Spectral Kurtosis Technology to Varying Operating Conditions.

Sensors (Basel, Switzerland)
In this paper, two novel consistency vectors are proposed, which when combined with appropriate machine learning algorithms, can be used to adapt the Spectral Kurtosis technology for optimum gearbox damage diagnosis in varying operating conditions. M...

Evaluation Technology of Classroom Students' Learning State Based on Deep Learning.

Computational intelligence and neuroscience
Facial features are an effective representation of students' fatigue state, and the eye is more closely related to fatigue state. However, there are three main problems in the existing research: (1) the positioning of the eye is vulnerable to the ext...