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Results for “Classification Algorithms”

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At least 865 records · Page 48Linked to original sources

PubMed1999

Leap-frog is a robust algorithm for training neural networks.

Optimization of perceptron neural network classifiers requires an optimization algorithm that is robust. In general, the best network is selected after a number of optimization trials. An effective optimization algorithm generates good weight-vector solutions in a few optimization trial runs owing to its inherent ability to escape local minima, where a less effective algorithm requires a larger number of trial runs. Repetitive training and testing is a tedious process, so that an effective algorithm is desirable to reduce training time and increase the quality of the set of available weight-vector solutions. We present leap-frog as a robust optimization algorithm for training neural networks. In this paper the dynamic principles of leap-frog are described together with experiments to show the ability of leap-frog to generate reliable weight-vector solutions. Performance histograms are used to compare leap-frog with a variable-metric method, a conjugate-gradient method with modified restarts, and a constrained-momentum-based algorithm. Results indicate that leap-frog performs better in terms of classification error than the remaining three algorithms on two distinctly different test problems.

Algorithms↗

PubMed1999

Automated comet assay analysis.

BACKGROUND: Recently the "comet assay" or "single-cell gel electrophoresis assay" has been established as a sensitive method for the detection of DNA damage and repair. Most of the software now available to quantify various parameters for DNA damage requires the interaction of a human observer. In this report, we describe an automated analysis system that is based on self-developed software and hardware and needs minimal human interaction. METHODS: The image analysis is divided into two parts: 1) automatic cell recognition and comet classification and 2) quantification of desired comet parameters. Image preprocessing, segmentation, and feature classification were developed with algorithms based on mathematical morphology. To enhance evaluation speed, we have introduced parallel processing of data under the Windows NT operating system (Microsoft Corporation, Redmond, WA). Use of an analogue real-time autofocus unit (Böcker et al.: Phys Med Biol 1997;42:1981-1992) allows for faster analysis. RESULTS: Our recognition software shows a sensitivity of 95.2% and a specificity of 92.7% when tested on test samples from routine work with DNA damage by low-dose radiation (0-2 Gy). The parallel hardware and software concept enables us to analyze 100 comets on one slide in less than 15 min. CONCLUSIONS: A comparison of measurements made on the same samples by manual and automated analysis systems revealed that there are no significant differences. The slope of the dose-response curves and the repair kinetics are very similar and demonstrate that automatic comet assay analysis is possible.

Algorithms↗

PubMed2000

How short can courses be in lower respiratory tract infections?

Prospective clinical studies conducted over the last 10 years provide data on which to base decisions regarding the treatment of community-acquired pneumonia (CAP), including the need for hospitalization, optimal timing of the switch from intravenous to oral antibiotic therapy and the discharge of patients. Validated treatment algorithms, such as the classification of community-acquired pneumonia, now enable decisions to be made on which patients with CAP require hospitalization, as well as identifying those who will benefit from early switch therapy. Generally, unstable CAP patients are suitable candidates for early switch therapy, which consists of rapid initiation of 1 - 2 days' intravenous therapy followed by 5 days' oral therapy, with early discharge from hospital after the receipt of one or two doses of oral antibiotic. Studies with intravenous cefuroxime and followed by oral cefuroxime axetil suggest this regimen is both effective and well tolerated as rapid switch therapy, and has the potential to reduce overall healthcare costs and improve patient satisfaction.

Anti-Bacterial Agents↗

PubMed2001

[Surgical treatment of obturation obstruction of the colon].

Treatment results of 336 patients with obturative obstruction of the colon were analyzed, stages of disease development were demonstrated (4 stages). Based on this classification treatment-diagnostic algorithm was developed, which permitted to make terms and scope of preoperative preparation more correct. Individualized preoperative policy and developed complex of inflammatory complications prophylaxis allowed to expand indications for radical operative interventions including combined operations to 85.1%. Only technically unremovable tumors and multiple distant metastases were contraindications for primary resections. Lethality decreased to 7.1%, local inflammatory complications--to 12.7%.

Adult↗

PubMed2001

[Current concepts in classification of lymphoid tissue tumors].

An analysis of the data of foreign literature and of the author's personal experiences allows a conclusion to be made concerning the evolution of views on lymphoid tissue tumors. The author proposes a classification of lymphomas, the algorithm of diagnosis of the lymphomas, describes certain clinical characteristics of different types of lymphomas.

Humans↗

PubMedDate not supplied

[Tree reconciliation: reconstruction of species evolution by phylogenetic gene trees].

It is well known that phylogenetic trees derived from different protein families are often incongruent. This is explained by mapping errors and by the essential processes of gene duplication, loss, and horizontal transfer. Therefore, the problem is to derive a "consensus" tree best fitting the given set of gene trees. This work presents a new method of deriving this tree. The method is different from the existing ones, since it considers not only the topology of the initial gene trees, but also the reliability of their branches. Thereby one can explicitly take into account the possible errors in the gene trees caused by the absence of reliable models of sequence evolution, by uneven evolution of different gene families and taxonomic groups, etc.

Algorithms↗

PubMed2004

Advances in biomedical image analysis--past, present and future challenges.

Starting from raw data files coding eight bits of gray values per image pixel and identified with no more than eight characters to refer to the patient, the study, and technical parameters of the imaging modality, biomedical imaging has undergone manifold and rapid developments. Today, rather complex protocols such as Digital Imaging and Communications in Medicine (DICOM) are used to handle medical images. Most restrictions to image formation, visualization, storage and transfer have basically been solved and image interpretation now sets the focus of research. Currently, a method-driven modeling approach dominates the field of biomedical image processing, as algorithms for registration, segmentation, classification and measurements are developed on a methodological level. However, a further metamorphosis of paradigms has already started. The future of medical image processing is seen in task-oriented solutions integrated into diagnosis, intervention planning, therapy and follow-up studies. This alteration of paradigms is also reflected in the literature. As German activities are strongly tied to the international research, this change of paradigm is demonstrated by selected papers from the German annual workshop on medical image processing collected in this special issue.

Electronic Data Processing↗

PubMed1992

Rapid classification of positive blood cultures. Prospective validation of a multivariate algorithm.

OBJECTIVE: To develop and validate a model predicting whether a positive blood culture represents a true positive or a contaminant in hospitalized patients, using only information available when the initial culture result becomes available. DESIGN: Prospective cohort study with derivation and validation sets. SETTING: Urban tertiary care hospital. PATIENTS: Clinical data were collected within 24 hours of the initial culture from a random sample of inpatients who had blood cultures performed, and data from the episodes in which growth was reported were included. There were 219 episodes in the derivation set and 129 episodes in the validation set. MAIN OUTCOME MEASURE: True bacteremia. Reviewers blinded to potential clinical predictors and initial laboratory results classified 115 (53%) of the episodes in the derivation set and 57 (44%) of the episodes in the validation set as true positives. RESULTS: Independent multivariate predictors of bacteremia were organism type, days until the blood culture became positive, multiple positive cultures, and clinical risk score. These factors were used to develop a model stratifying patients into four risk groups. In the derivation set's lowest-risk group, 92% (65/71) of positives represented contaminants, and in the highest-risk group, 97% (86/89) of positives represented true positives. In the validation set, the misclassification rates were 14% (8/59) in the low-risk group, and 11% (5/44) in the high-risk group. These two groups together comprised 76% of all episodes. CONCLUSION: This model can help clinicians quantify the likelihood that a given positive blood culture represents a true positive when the laboratory first calls, which may be helpful in subsequent decision making.

Adult↗

PubMed2005

Utilizing the UMLS for semantic mapping between terminologies.

An algorithm was derived to find candidate mappings between any two terminologies inside the UMLS, making use of synonymy, explicit mapping relations and hierarchical relationships among UMLS concepts. Using an existing set of mappings from SNOMED CT to ICD9CM as our gold standard, we managed to find candidate mappings for 86% of SNOMED CT terms, with recall of 42% and precision of 20%. Among the various methods used, mapping by UMLS synonymy was particularly accurate and could potentially be useful as a quality assurance tool in the creation of mapping sets or in the UMLS editing process. Other strengths and weaknesses of the algorithm are discussed.

Algorithms↗

PubMedDate not supplied

[The assessment of the clinical status of patients with alveolar hydatid disease by using statistical processing methods. 2. The correlation of laboratory tests at different disease stages and their clinical interpretation].

In 44 patients with alveolar echinococcosis, the correlation between the results of main laboratory tests were studied and their clinical interpretation was given. It was shown that at an uncomplicated stage of the disease, the immune response suppressing the helminth growth plays the main role; at the stage of complications the pathogenetic significance of non-specific inflammatory responses caused by destructive processes increases; at a stage of decompensation the correlation reflects severe immunological abnormalities and progressive immunodepression. The obtained correlations might be used as a measure for determining the stage of the disease in the algorithmic method for the classification of alveolar echinococcosis.

Echinococcosis, Hepatic↗

PubMedDate not supplied

Computerized interactive morphometry of brushing cytology specimens.

Forty-two bronchial brushing cytology specimens were evaluated by a video-based computerized interactive morphometry (CIM) system with an interactive peripheral consisting of a touch-sensitive screen mounted over a high-resolution video monitor. The system was programmed to allow a trained observer to rapidly measure nuclear and cytoplasmic profile diameters of randomly selected cells and to calculate their nuclear-cytoplasmic ratios. The specimens included 13 cytologic slides with no malignant cells present, 14 with non-small cell carcinoma cells and 15 with small cell carcinoma cells. The cases were divided into two groups: a training set composed of slides with "known diagnosis" and a test set of slides with "unknown diagnosis". A data set was constructed with the measurements from the cases with "known diagnosis," and an algorithm that allowed the classification of cases by hierarchical analysis was developed. The data was also analyzed with statistical methods of classificatory discriminant analysis. Utilizing the information in the data base, the slides with "unknown diagnosis" were classified individually; all cases were correctly classified by the procedures. Potential applications of CIM in cytology are discussed.

Bronchi↗

PubMed1988

[Algorithms for constructing phylogenetic trees of maximum topological similarity].

The paper concerns the practical realization of the maximum topologic similarity principle for phylogenetic reconstruction. This novel principle is described in the accompanying paper. Two algorithms that were embodied in the computer program allow one to find out the unique tree in case when source data admit the existence of such tree. In case if numerous parallel mutations make such precise realization impossible, algorithms allow one to obtain approximations to the maximum topologic similarity trees with a high computation efficiency. Examples illustrating use of these algorithms, as well as discussion of biological consistency of the novel concept are presented.

Algorithms↗

PubMed1987

TurboTree: a fast algorithm for minimal trees.

A branch and bound algorithm is described for searching rapidly for minimal length trees from biological data. The algorithm adds characters one at a time, rather than adding taxa, as in previous branch and bound methods. The algorithm has been programmed and is available from the authors. A worked example is given with 33 characters and 15 taxa. About 8 x 10(12) binary trees are possible with 15 taxa but the branch and bound program finds the minimal tree in less than 5 min on an IBM PC.

Algorithms↗

PubMedDate not supplied

[Statistical characteristics in primary structures of functional regions of Escherichia coli genome. II. Non-stationary Markov chains].

We introduced non-stationary Marcov chains for statistical description of the DNA E. coli structural domains. The values of all needed parameters for those chains was determined by the preliminary statistical processing of a wide set of the E. coli coding regions. It was shown that non-stationary models predict frequencies of occurrences of various combinations of nucleotides within the coding fragments of DNA, better than stationary ones. In particular non-stationary models give good approximation for short and long distance arrangement of nucleotides in the coding regions. The correlation parameters for neighbour codons and for neighbour amino acid residuals in E. coli protein's primary structure was determined from the non-stationary model of the second order. With the aid of the statistical criteria it was found that neighbour residuals in polypeptide chains can't be considered as independent. The new model of the DNA structural domain may be used in computer algorithms for recognition and classification of DNA functional regions.

Base Sequence↗

PubMed1995

Interpretation of diagnostic implications of fluorescence parameters for atherosclerosis in fibrous, calcified and normal arteries.

Fluorescence spectroscopy presents great interest for the diagnosis of atherosclerosis. Nevertheless there are some difficulties in the interpretation of diagnostic information. This could be overcome by precise methods of extraction of the diagnostic parameters and convenient statistical analysis, which are the subject of this work. Fluorescence excitation-emission matrices from different categories of coronary arteries were developed and used to derive the optimum excitation wavelength on the one hand and to assign the spectra to specific chromophores on the other hand. Simple dimensionless functions (Fi) were formed by the ratio of the intensities at selected wavelength and the logistic model was used for statistical analysis. Decision surfaces were drawn and it was estimated that the probability of correct classification is 88%. The algorithm correctly diagnoses 97% of healthy from diseased samples and 80% of fibrous from calcified coronary arteries.

Algorithms↗

PubMed1998

Morphological analysis and classification of latent prostate cancer using a 3-dimensional computer algorithm: analysis of tumor volume, grade, tumor doubling time and life expectancy.

PURPOSE: We estimate the potential clinical significance of prostate cancers found at autopsy provided the individual had lived to the projected lifespan based on life expectancy tables. MATERIALS AND METHODS: We used 3-dimensional computer models of 59 autopsy prostates that contained clinically undetected carcinoma to determine tumor volumes. Using doubling times of 2, 3, 4 and 6 years, carcinoma volumes at autopsy were extrapolated through patient projected lifespans. The carcinomas were then classified as clinically insignificant or significant according to Mayo Clinic criteria. RESULTS: In 13 patients less than 60 years old, using doubling times of 2, 3, 4 and 6 years, clinically significant tumors were identified in 13 (100%), 10 (77%), 7 (54%) and 7 (54%), respectively. In 46 patients 60 years old or greater significant tumors were identified in 32 (70%), 22 (48%), 21 (46%) and 18 (39%), respectively. A statistical difference (p <0.0001) was found between the mean tumor volume (0.20 +/- 0.10 cc) of 43 organ confined carcinomas and the mean tumor volume (3.26 +/- 3.58 cc) of 16 extracapsular tumors. No capsule perforation was found in tumors with Gleason sums of 4 or less. However, capsule perforation was present in 8 of 31 tumors (25.8%) with Gleason sums of 5 or 6, and 8 of 11 tumors (72.7%) with Gleason scores of 7 or 8. CONCLUSIONS: Prostatic carcinomas that remain clinically insignificant throughout life are likely to have doubling times greater than 4 years. The subset of carcinomas that emerge as clinically significant are likely to have doubling times less than 3 years. Therefore, an accurate method to measure doubling time at diagnosis could, provide an objective indicator to guide clinical management.

Adult↗

PubMed1995

Discriminant classification of motor unit potentials (MUPs) successfully separates neurogenic and myopathic conditions. A comparison of multi- and univariate diagnostical algorithms for MUP analysis.

Multivariate statistical methods may be more appropriate for the multidimensional material of quantitative motor unit potential (MUP) analysis than the multiple univariate tests of the conventional Buchthal analysis. Buchthal analysis was slightly modified before it was used as the gold standard for new multivariate diagnostical algorithms, based on principal component analysis and on MUP discriminant classification: muscle means of continuous variables were related to tolerance limits after adequate transformation. Chi-square tests were used for dichotomized variables, e.g., polyphasia. Sensitivity and specificity of the uni- and multivariate algorithms were compared for 539 muscles from patients with motor neuron diseases, neuropathies and myopathies and for 91 biceps brachii, rectus femoris and tibialis anterior control muscles. False positive results accumulated less than expected by repeat univariate tests for single MUP parameters, due to high correlation. Combination of single parameters to factor scores did not improve specificity. One advantage of factor analysis was that factor matrix and factor scores matched those of previous studies in spite of different input parameters, which may facilitate multicenter comparisons. Discriminant classification successfully separated neurogenic and myopathic conditions, even in myositic muscles and motor neuron diseases, where myopathic and neuropathic MUPs frequently intermingle. Discriminant classification may support expert decisions and add weight to EMG differential diagnosis.

Adult↗

PubMed2004

Mu rhythm-based cursor control: an offline analysis.

OBJECTIVE: To classify the EEG data recorded in mu rhythm-based cursor control experiments with 4 possible choices. METHODS: The algorithm included preprocessing, feature extraction, and classification. Two spatial filters, common average reference and common spatial subspace decomposition, were used in preprocessing to improve the signal-to-noise ratio, and then two features were extracted based on the power spectrum and the time course of the mu rhythm respectively. A Fisher ratio was defined to select channels in feature extraction. A 2-dimensional linear classifier was trained for final classification. RESULTS: Two types of classifiers were trained for the training dataset. The uniform classifier gave a classification accuracy of 76.4%, and the classifier trained by leave-one-out method gave a classification accuracy of 74.4%, both higher than the online accuracy 69.5%. The uniform classifier was applied to the test dataset and the classification accuracy was 65.9%, lower than the online accuracy 73.2%. CONCLUSIONS: Spatial filtering can give a notable improvement in classification accuracy. The time course of the mu rhythm, as well as the power of the mu rhythm, shows difference between the 4 targets, and can contribute to the classification. SIGNIFICANCE: The spatial filtering, feature extraction and channel selection methods in the algorithm will provide some practical suggestions for further study on the mu rhythm-based brain-computer interface.

Algorithms↗