AIM portraits: tracing the evolution of artificial intelligence in medicine and predicting its future in the new millennium.
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Artificial Intelligence↗
Biomedical subjects
N Lavrac
Publications and source records attributed to N Lavrac.
Data mining techniques and applications in medicine.
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Artificial Intelligence↗
Selected techniques for data mining in medicine.
Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis to be coupled with methods for efficient computer-assisted analysis. This paper presents selected data mining techniques that can be applied in medicine, and in particular some machine learning techniques including the mechanisms that make them better suited for the analysis of medical databases (derivation of symbolic rules, use of background knowledge, sensitivity and specificity of induced descriptions). The importance of the interpretability of results of data analysis is discussed and illustrated on selected medical applications.
Adult↗
Use of functional electrical stimulation in the lower extremities of incomplete spinal cord injured patients.
After a program of therapeutic electrical stimulation, 3 groups of incomplete spinal cord injured (SCI) patients were identified, those in whom an improvement of both voluntary and stimulated muscle force was observed, those with an increase in stimulation response only, and patients in whom no effect of electrical stimulation training could be recorded. As it is difficult to predict the outcome of the electrical stimulation rehabilitation process, a diagnostic procedure was developed to predict soon after accidents which incomplete SCI patients are candidates for permanent use of a functional electrical stimulation (FES) orthotic aid. The candidates for chronic use of FES are patients with weak ankle dorsiflexors and sufficiently strong knee extensors. These patients are equipped with a single channel peroneal stimulator augmenting dorsiflexion and knee and hip flexion in a total lower limb flexion response. By applying FES to the ankle plantar flexors, the swing phase of walking can be significantly shortened and faster walking obtained.
Ankle Joint↗
Induction of decision trees and Bayesian classification applied to diagnosis of sport injuries.
Machine learning techniques can be used to extract knowledge from data stored in medical databases. In our application, various machine learning algorithms were used to extract diagnostic knowledge which may be used to support the diagnosis of sport injuries. The applied methods include variants of the Assistant algorithm for top-down induction of decision trees, and variants of the Bayesian classifier. The available dataset was insufficient for reliable diagnosis of all sport injuries considered by the system. Consequently, expert-defined diagnostic rules were added and used as pre-classifiers or as generators of additional training instances for diagnoses for which only few training examples were available. Experimental results show that the classification accuracy and the explanation capability of the naive Bayesian classifier with the fuzzy discretization of numerical attributes were superior to other methods and estimated as the most appropriate for practical use.
Artificial Intelligence↗
Rule induction and instance-based learning applied in medical diagnosis.
Machine learning methods have been applied in a variety of medical domains in order to improve medical decision making. Improved medical diagnosis and prognosis can be achieved through automatic analysis of patient data stored in medical records, i.e., by learning from past experience. Given patient records with corresponding diagnoses, machine learning methods are able to classify new cases either through constructing explicit rules that generalize the training cases (e.g., rule induction) or by storing (some of) the training cases for reference (instance-based learning). This paper presents the methodologies of rule induction and instance-based learning and their application to medical diagnosis, in particular, the problem of early diagnosis of rheumatic diseases. It also discusses the possibility to use existing expert knowledge to support the learning process and the utility of such knowledge.
Algorithms↗