AIMC Topic: Machine Learning

Clear Filters Showing 16191 to 16200 of 34417 articles

A Learning-Based Approach to Sensorize Soft Robots.

Soft robotics
Soft actuators and their sensors have always been separate entities with two distinct roles. The omnidirectional compliance of soft robots thus means that multiple sensors have to be used to sense different modalities in the respective planes of moti...

Optimizing discharge after major surgery using an artificial intelligence-based decision support tool (DESIRE): An external validation study.

Surgery
BACKGROUND: In the DESIRE study (Discharge aftEr Surgery usIng aRtificial intElligence), we have previously developed and validated a machine learning concept in 1,677 gastrointestinal and oncology surgery patients that can predict safe hospital disc...

Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Artificial intelligence (AI) techniques have emerged as a highly efficient approach to accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear cardiology. In nuclear cardiology, there are many clinical, stress, and im...

AMPpred-EL: An effective antimicrobial peptide prediction model based on ensemble learning.

Computers in biology and medicine
Antimicrobial peptides (AMPs) are important for the human immune system and are currently applied in clinical trials. AMPs have been received much attention for accurate recognition. Recently, several computational methods for identifying AMPs have b...

Rainfall Prediction System Using Machine Learning Fusion for Smart Cities.

Sensors (Basel, Switzerland)
Precipitation in any form-such as rain, snow, and hail-can affect day-to-day outdoor activities. Rainfall prediction is one of the challenging tasks in weather forecasting process. Accurate rainfall prediction is now more difficult than before due to...

Fusing pre-trained convolutional neural networks features for multi-differentiated subtypes of liver cancer on histopathological images.

BMC medical informatics and decision making
Liver cancer is a malignant tumor with high morbidity and mortality, which has a tremendous negative impact on human survival. However, it is a challenging task to recognize tens of thousands of histopathological images of liver cancer by naked eye, ...

Studying and mitigating the effects of data drifts on ML model performance at the example of chemical toxicity data.

Scientific reports
Machine learning models are widely applied to predict molecular properties or the biological activity of small molecules on a specific protein. Models can be integrated in a conformal prediction (CP) framework which adds a calibration step to estimat...

A catalogue with semantic annotations makes multilabel datasets FAIR.

Scientific reports
Multilabel classification (MLC) is a machine learning task where the goal is to learn to label an example with multiple labels simultaneously. It receives increasing interest from the machine learning community, as evidenced by the increasing number ...

Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions.

Physical chemistry chemical physics : PCCP
While state-of-art models can predict reactions through the transfer learning of thousands of samples with the same reaction types as those of the reactions to predict, how to prepare such models to predict "unseen" reactions remains an unanswered qu...