AIMC Topic: Algorithms

Clear Filters Showing 14081 to 14090 of 28713 articles

Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation method.

Scientific reports
We developed and validated a deep learning (DL)-based model using the segmentation method and assessed its ability to detect lung cancer on chest radiographs. Chest radiographs for use as a training dataset and a test dataset were collected separatel...

Review on generic methods for mechanical modeling, simulation and control of soft robots.

PloS one
In this review paper, we are interested in the models and algorithms that allow generic simulation and control of a soft robot. First, we start with a quick overview of modeling approaches for soft robots and available methods for calculating the mec...

COVID-19 Related Sentiment Analysis Using State-of-the-Art Machine Learning and Deep Learning Techniques.

Frontiers in public health
The coronavirus disease 2019 (COVID-19) pandemic has influenced the everyday life of people around the globe. In general and during lockdown phases, people worldwide use social media network to state their viewpoints and general feelings concerning t...

[Development and evaluation of a deep learning algorithm for German word recognition from lip movements].

HNO
BACKGROUND: When reading lips, many people benefit from additional visual information from the lip movements of the speaker, which is, however, very error prone. Algorithms for lip reading with artificial intelligence based on artificial neural netwo...

A deep learning model for screening type 2 diabetes from retinal photographs.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: We aimed to develop and evaluate a non-invasive deep learning algorithm for screening type 2 diabetes in UK Biobank participants using retinal images.

Ligand Based Virtual Screening Using Self-organizing Maps.

The protein journal
Conventional drug discovery methods rely primarily on in-vitro experiments with a target molecule and an extensive set of small molecules to choose the suitable ligand. The exploration space for the selected ligand being huge; this approach is highly...

Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network.

Sensors (Basel, Switzerland)
Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers....

Providing Fault Detection from Sensor Data in Complex Machines That Build the Smart City.

Sensors (Basel, Switzerland)
Household appliances, climate control machines, vehicles, elevators, cash counting machines, etc., are complex machines with key contributions to the smart city. Those devices have limited memory and processing power, but they are not just actuators;...

Application of machine learning missing data imputation techniques in clinical decision making: taking the discharge assessment of patients with spontaneous supratentorial intracerebral hemorrhage as an example.

BMC medical informatics and decision making
BACKGROUND: There are often many missing values in medical data, which directly affect the accuracy of clinical decision making. Discharge assessment is an important part of clinical decision making. Taking the discharge assessment of patients with s...

Intelligent Diagnosis Method for New Diseases Based on Fuzzy SVM Incremental Learning.

Computational and mathematical methods in medicine
The diagnosis of new diseases is a challenging problem. In the early stage of the emergence of new diseases, there are few case samples; this may lead to the low accuracy of intelligent diagnosis. Because of the advantages of support vector machine (...