AIMC Topic: Machine Learning

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Detecting Human Actions in Drone Images Using YoloV5 and Stochastic Gradient Boosting.

Sensors (Basel, Switzerland)
Human action recognition and detection from unmanned aerial vehicles (UAVs), or drones, has emerged as a popular technical challenge in recent years, since it is related to many use case scenarios from environmental monitoring to search and rescue. I...

Artificial Intelligence in Spinal Imaging: Current Status and Future Directions.

International journal of environmental research and public health
Spinal maladies are among the most common causes of pain and disability worldwide. Imaging represents an important diagnostic procedure in spinal care. Imaging investigations can provide information and insights that are not visible through ordinary ...

Predicting conversion to Alzheimer's disease in individuals with Mild Cognitive Impairment using clinically transferable features.

Scientific reports
Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer's disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well established in the brain. He...

Efficacy and pitfalls of digital technologies in healthcare services: A systematic review of two decades.

Frontiers in public health
The use of technology in the healthcare sector and its medical practices, from patient record maintenance to diagnostics, has significantly improved the health care emergency management system. At that backdrop, it is crucial to explore the role and ...

Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification Model.

Computational intelligence and neuroscience
Esophageal cancer (EC) is a commonly occurring malignant tumor that significantly affects human health. Earlier recognition and classification of EC or premalignant lesions can result in highly effective targeted intervention. Accurate detection and ...

Artificial intelligence and machine learning applications in biopharmaceutical manufacturing.

Trends in biotechnology
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biother...

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis.

Environmental science and pollution research international
The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper emplo...

Interpretable machine learning framework reveals microbiome features of oral disease.

Microbiological research
BACKGROUND: Although the oral microbiome plays an important role in the progression of oral diseases, the microbes closely related to these diseases remain largely uncharacterized.

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning.

Nature biomedical engineering
In tasks involving the interpretation of medical images, suitably trained machine-learning models often exceed the performance of medical experts. Yet such a high-level of performance typically requires that the models be trained with relevant datase...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Computers in biology and medicine
Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in m...