AIMC Topic: Algorithms

Clear Filters Showing 12111 to 12120 of 28713 articles

A novel approach for COVID-19 Infection forecasting based on multi-source deep transfer learning.

Computers in biology and medicine
COVID-19 is a contagious disease; so, predicting its future infections in a provincial region requires the consideration of the related data (i.e., rates of infection, mortality and recovery, etc.) over a period of time. Clearly, the COVID-19 data of...

I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.

Nature protocols
Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-d...

A learning-based, region of interest-tracking algorithm for catheter detection in echocardiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Echocardiography (echo) is gaining popularity to guide the catheter during surgical procedures. However, it is difficult to discern the catheter tip in echo even with an acoustically active catheter. An acoustically active catheter is detected for th...

Optimization assisted framework for thyroid detection and classification: A new ensemble technique.

Gene expression patterns : GEP
Ultrasound (US) is an inexpensive and non-invasive technique for capturing the image of the thyroid gland and nearby tissue. The classification and detection of thyroid disorders is still in its infant stage. This study aims to present a new thyroid ...

Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring.

Sensors (Basel, Switzerland)
Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into its individual sub-components. Over the years, signal processing and machine learning algorithms have been combined to achieve this. Many publications...

Crop Mapping Using the Historical Crop Data Layer and Deep Neural Networks: A Case Study in Jilin Province, China.

Sensors (Basel, Switzerland)
Machine learning combined with satellite image time series can quickly, and reliably be implemented to map crop distribution and growth monitoring necessary for food security. However, obtaining a large number of field survey samples for classifier t...

Human-Robot Collaboration in Industrial Automation: Sensors and Algorithms.

Sensors (Basel, Switzerland)
Technology is changing the manufacturing world [...].

Development of a Spine X-Ray-Based Fracture Prediction Model Using a Deep Learning Algorithm.

Endocrinology and metabolism (Seoul, Korea)
BACKGRUOUND: Since image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data.

Artificial intelligence in emergency radiology: A review of applications and possibilities.

Diagnostic and interventional imaging
Artificial intelligence (AI) applications in radiology have been rising exponentially in the last decade. Although AI has found usage in various areas of healthcare, its utilization in the emergency department (ED) as a tool for emergency radiologist...

Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.

Surgical endoscopy
BACKGROUND: Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and im...