AIMC Topic: Machine Learning

Clear Filters Showing 16431 to 16440 of 34417 articles

Temporal shift and predictive performance of machine learning for heart transplant outcomes.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: Outcome prediction following heart transplant is critical to explaining risks and benefits to patients and decision-making when considering potential organ offers. Given the large number of potential variables to be considered, this task ...

A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management.

Medicina (Kaunas, Lithuania)
Nowadays, Artificial Intelligence (AI) and its subfields, Machine Learning (ML) and Deep Learning (DL), are used for a variety of medical applications. It can help clinicians track the patient's illness cycle, assist with diagnosis, and offer appropr...

Upper and Lower Leaf Side Detection with Machine Learning Methods.

Sensors (Basel, Switzerland)
Recent studies have approached the identification of foliar plant diseases using artificial intelligence, but in these works, classification is achieved using only one side of the leaf. Phytopathology specifies that there are diseases that show simil...

Machine learning to predict effective reaction rates in 3D porous media from pore structural features.

Scientific reports
Large discrepancies between well-mixed reaction rates and effective reactions rates estimated under fluid flow conditions have been a major issue for predicting reactive transport in porous media systems. In this study, we introduce a framework that ...

A framework for rigorous evaluation of human performance in human and machine learning comparison studies.

Scientific reports
Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, the...

ENNGene: an Easy Neural Network model building tool for Genomics.

BMC genomics
BACKGROUND: The recent big data revolution in Genomics, coupled with the emergence of Deep Learning as a set of powerful machine learning methods, has shifted the standard practices of machine learning for Genomics. Even though Deep Learning methods ...

Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries.

Journal of healthcare engineering
BACKGROUND: Dental caries is one of the major oral health problems and is increasing rapidly among people of every age (children, men, and women). Deep learning, a field of Artificial Intelligence (AI), is a growing field nowadays and is commonly use...

An analysis framework for clustering algorithm selection with applications to spectroscopy.

PloS one
Cluster analysis is a valuable unsupervised machine learning technique that is applied in a multitude of domains to identify similarities or clusters in unlabelled data. However, its performance is dependent of the characteristics of the data it is b...

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cerebellar ataxia (CA) is concerned with the incoordination of movement caused by cerebellar dysfunction. Movements of the eyes, speech, trunk, and limbs are affected. Conventional machine learning approaches utilizing centralised databases have been...