Medical imaging using machine learning and deep learning algorithms: a review
Machine and deep learning algorithms are rapidly growing in dynamic research of medical
imaging. Currently, substantial efforts are developed for the enrichment of medical imaging …
imaging. Currently, substantial efforts are developed for the enrichment of medical imaging …
Machine learning for medical diagnosis: history, state of the art and perspective
I Kononenko - Artificial Intelligence in medicine, 2001 - Elsevier
The paper provides an overview of the development of intelligent data analysis in medicine
from a machine learning perspective: a historical view, a state-of-the-art view, and a view on …
from a machine learning perspective: a historical view, a state-of-the-art view, and a view on …
Towards automatic polyp detection with a polyp appearance model
This work aims at automatic polyp detection by using a model of polyp appearance in the
context of the analysis of colonoscopy videos. Our method consists of three stages: region …
context of the analysis of colonoscopy videos. Our method consists of three stages: region …
Heterogeneous uncertainty sampling for supervised learning
DD Lewis, J Catlett - Machine learning proceedings 1994, 1994 - Elsevier
Uncertainty sampling methods iteratively request class labels for training instances whose
classes are uncertain despite the previous labeled instances. These methods can greatly …
classes are uncertain despite the previous labeled instances. These methods can greatly …
Inductive Logic Programming.
N Lavrac, S Dzeroski - WLP, 1994 - Springer
The 18th International Conference on Inductive Logic Programming was held in Prague,
September 10–12, 2008. ILP returned to Prague after 11 years, and it is tempting to look at …
September 10–12, 2008. ILP returned to Prague after 11 years, and it is tempting to look at …
A critical review for developing accurate and dynamic predictive models using machine learning methods in medicine and health care
HO Alanazi, AH Abdullah, KN Qureshi - Journal of medical systems, 2017 - Springer
Abstract Recently, Artificial Intelligence (AI) has been used widely in medicine and health
care sector. In machine learning, the classification or prediction is a major field of AI. Today …
care sector. In machine learning, the classification or prediction is a major field of AI. Today …
Inductive and Bayesian learning in medical diagnosis
I Kononenko - Applied Artificial Intelligence an International …, 1993 - Taylor & Francis
Although successful in medical diagnostic problems, inductive learning systems were not
widely accepted in medical practice. In this paper two different approaches to machine …
widely accepted in medical practice. In this paper two different approaches to machine …
Machine learning in medical applications
GD Magoulas, A Prentza - Advanced course on artificial intelligence, 1999 - Springer
Abstract Machine Learning (ML) provides methods, techniques, and tools that can help
solving diagnostic and prognostic problems in a variety of medical domains. ML is being …
solving diagnostic and prognostic problems in a variety of medical domains. ML is being …
Segmentation of color fundus images of the human retina: Detection of the optic disc and the vascular tree using morphological techniques
T Walter, JC Klein - International symposium on medical data analysis, 2001 - Springer
This paper presents new algorithms based on mathematical morphology for the detection of
the optic disc and the vascular tree in noisy low contrast color fundus photographs. Both …
the optic disc and the vascular tree in noisy low contrast color fundus photographs. Both …
Propositionalization approaches to relational data mining
This chapter surveys methods that transform a relational representation of a learning
problem into a propositional (feature-based, attributevalue) representation. This kind of …
problem into a propositional (feature-based, attributevalue) representation. This kind of …