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Results for “Classification Algorithms”

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PubMed1997

Digital tomosynthesis in breast imaging.

PURPOSE: To describe and evaluate a method of tomosynthesis breast imaging with a full-field digital mammographic system. MATERIALS AND METHODS: In this tomosynthesis method, low-radiation-dose images were acquired as the x-ray source was moved in an arc above the stationary breast and digital detector. A step-and-expose method of imaging was used. Breast tomosynthesis and conventional images of two imaging phantoms and four mastectomy specimens were obtained. Three experienced readers scored the relative lesion visibility, lesion margin visibility, and confidence in the classification of six lesions. RESULTS: Tomosynthesis image-reconstruction algorithms allow tomographic imaging of the entire breast from a single arc of the x-ray source and at a radiation dose comparable with that in single-view mammography. Except for images of a large mass in a fatty breast, the tomosynthesis images were superior to the conventional images. CONCLUSION: Digital mammographic systems make breast tomosynthesis possible. Tomosynthesis may improve the specificity of mammography with improved lesion margin visibility and may improve early breast cancer detection, especially in women with radiographically dense breasts.

Female↗

PubMed2001

Microarray analysis of trophoblast differentiation: gene expression reprogramming in key gene function categories.

Placental development results from a highly dynamic differentiation program. We used DNA microarray analysis to characterize the process by which human cytotrophoblast cells differentiate into syncytiotrophoblast cells in a purified cell culture system. Of 6,918 genes analyzed, 141 genes were induced and 256 were downregulated by more than 2-fold. Dynamically regulated genes were divided by the K-means algorithm into 9 kinetic pattern groups, then by biologic classification into 6 overall functional categories: cell and tissue structural dynamics, cell cycle and apoptosis, intercellular communication, metabolism, regulation of gene expression, and expressed sequence tag (EST) and function unknown. Gene expression changes within key functional categories were tightly coupled to morphological changes. In several key gene function categories, such as cell and tissue structure, many gene members of the category were strongly activated while others were strongly repressed. These findings suggest that differentiation is augmented by "categorical reprogramming" in which the function of induced genes is enhanced by preventing the further synthesis of categorically related gene products.

Cell Differentiation↗

PubMedDate not supplied

Stability and interpersonal agreement of the interview-based diagnosis of autism.

Interpersonal agreement and stability of the Autism Diagnostic Interview-Revised (ADI-R) was examined in this study. Four raters judging 55 subjects agreed moderately to excellently on the items of the diagnostic algorithm, operationalizing the main autistic symptoms according to the classification guidelines of ICD-10 and DSM-IV. When retesting 33 individuals, some items revealed only weak stability. On the level of domains of autistic behavior and diagnosis, the interrater reliability and retest reliability were consistently convincing.

Adolescent↗

PubMed1996

Juvenile rheumatoid arthritis.

Musculoskeletal problems account for the majority of initial complaints attended to by primary care physicians. It is likely that a child who eventually has juvenile rheumatoid arthritis diagnosed will initially be evaluated by a family physician or a pediatrician. Primary care physicians will play an increasingly important role in management of juvenile rheumatoid arthritis, as the availability of specialists in many communities is limited, and access to them may be further limited by managed care initiatives. This article offers a brief review of the definition and classification of juvenile rheumatoid arthritis and introduces a diagnostic algorithm to provide a simplified approach toward evaluating children with arthritis. Treatment and outcomes are summarized in text and graphic formats.

Age of Onset↗

PubMed1983

The study of depressive disorders using the PSE-ID-CATEGO system.

The PSE-CATEGO-ID system and its approach to the sub-classification of depression is described. The principle of sub-classification partly corresponds to the empirical relationships between symptoms on affective disorder. Comparison of CATEGO and DSM III demonstrates that major differences of classification can arise because of differences of the classificatory algorithm even though similar lists of symptoms are used. Empirical studies of the PSE-CATEGORO-ID system are described and their importance in providing evidence for a rational choice between classificatory system is emphasised.

Anxiety Disorders↗

PubMed1995

Gunshot wounds to the elbow.

Gunshot wound injuries to the elbow are rare. This article presents the experience of the King/Drew Medical Center. Classification and management of these injuries are emphasized. An algorithm is presented.

Adult↗

PubMed2001

The use of 1H magnetic resonance spectroscopy in inflammatory bowel diseases: distinguishing ulcerative colitis from Crohn's disease.

OBJECTIVES: The distinction between the two major forms of inflammatory bowel diseases (IBD), i.e., ulcerative colitis (UC) and Crohn's disease is sometimes difficult and may lead to a diagnosis of indeterminate colitis. We have used 1H magnetic resonance spectroscopy (MRS) combined with multivariate methods of spectral data analysis to differentiate UC from Crohn's disease and to evaluate normal-appearing mucosa in IBD. METHODS: Colon mucosal biopsies (45 UC and 31 Crohn's disease) were submitted to 1H MRS, and multivariate analysis was applied to distinguish the two diseases. A second study was performed to test endoscopically and histologically normal biopsies from IBD patients. A classifier was developed by training on 101 spectra (76 inflamed IBD tissues and 25 normal control tissues). The spectra of 38 biopsies obtained from endoscopically and histologically normal areas of the colons of patients with IBD were put into the validation test set. RESULTS: The classification accuracy between UC and Crohn's disease was 98.6%, with only one case of Crohn's disease and no cases of UC misclassified. The diagnostic spectral regions identified by our algorithm included those for taurine, lysine, and lipid. In the second study, the classification accuracy between normal controls and IBD was 97.9%. Only 47.4% of the endoscopically and histologically normal IBD tissue spectra were classified as true normals; 34.2% showed "abnormal" magnetic resonance spectral profiles, and the remaining 18.4% could not be classified unambiguously. CONCLUSIONS: There is a strong potential for MRS to be used in the accurate diagnosis of indeterminate colitis; it may also be sensitive in detecting preclinical inflammatory changes in the colon.

Adult↗

PubMed1980

Further experience with computer-assisted diagnosis of diseases of the liver and biliary tree.

Computer-assisted classification of disease has largely relied upon testing the diagnostic algorithm in the same population from which it was originally derived, as a means of validation. To evaluate the accuracy of a diagnostic program in which discriminant function analysis is used, we applied it to a separate population, selected by different criteria from those used to define the original case material on which the diagnostic program was based. We selected a group of 315 patients having abnormal values for alkaline phosphatase, bilirubin, or aspartate aminotransferase for further biochemical and immunological investigations. We used a computer program involving discriminant function analysis and classification procedures primed with the results of 10 tests obtained on each of 535 patients in a previous series to allocate those 173 new patients who had diseases of the liver or biliary tree into one of 13 disease groups. The classification was less accurate than was the case in previous cross-validation studies. We developed new discriminants with the new case material, using the same group of tests, and when cross-validation was performed, overall accuracy was greatly improved. These experiences point to the powerful influence of group selection upon computer-assisted diagnostic procedures, and the hazards of applying to one clinical population discriminant functions derived from a different population.

Autoanalysis↗

PubMed1999

[The concept and use of artificial neural networks in medicine].

The use of neural networks in medicine is concentrated mainly on classification purposes. In particular, neural networks applications in spectroscopy are discussed, where this approach offers powerful algorithmic tools for interpretation of spectral data and elucidation of chemical structure of compounds. Neural networks are effective also for the classification and prediction of chemical reactivity and structure of proteins and also for QSAR and QSRR studies. At present the most successful use of neural networks in clinical medicine is image analysis and analysis of wave forms--ECG or EEG pattern recognition and classification and partly also clinical diagnosis and prognosis. (Tab. 7, Fig. 2, Ref. 170.)

Neural Networks, Computer↗

PubMed2000

Relationship between ultrasound texture classification images and histology of atherosclerotic plaque.

Structure and content of atherosclerotic plaque varies between patients and may be indicative of their risk for embolisation. This study aimed to construct parametric images of B-scan texture and assess their potential for predicting plaque morphology. Sequential transverse in vitro scans of 10 carotid plaques, excised during endarterectomy, were compared with macrohistology maps of plaque content. Multidiscriminant analysis combined the output of 157 statistical and textural algorithms into five separate texture classes, displayed as ultrasound (US) texture classification images (UTCI). Visual comparison between corresponding UTCI and histology maps found the five texture classes matched with the location of fibrin, elastin, calcium, haemorrhage or lipid. However, histology preparation removes calcium and lipid and, so, can affect the structural integrity of atherosclerotic plaques. Soft tissue regions smaller than the UTCI kernel, (0.87 mm x 0.85 mm x 3.9 mm), such as blood clots, are also difficult to detect by UTCI. These factors demonstrate limitations in the use of histology as a "gold standard" for US tissue characterisation.

Arteriosclerosis↗

PubMed2000

EEG-based discrimination between imagination of left and right hand movements using Adaptive Gaussian Representation.

This article uses the Adaptive Gaussian Representation (AGR) for human electroencephalogram (EEG) feature extraction aiming the discrimination among mental tasks to be used in a brain computer interface (BCI). It does not focus on the AGR time-frequency representation, but rather on their projection coefficients. Ten volunteers were asked to imagine either right or left hand movement, according to a proper visual stimulus. The features of the resulting EEG signals were characterised by extracting AGR coefficients. Classification was carried out using a Multilayer perceptron (MLP) trained with the classical backpropagation algorithm. Overall results show that AGR coefficients representation is able to reveal a significant EEG discrimination between imagination of right and left hand movement with a mean classification performance of 91%+/-5.8% achieved for female subjects and 87%+/-5.0% achieved for male subjects.

Adult↗

PubMed1999

Classification of Arabidopsis thaliana gene sequences: clustering of coding sequences into two groups according to codon usage improves gene prediction.

While genomic sequences are accumulating, finding the location of the genes remains a major issue that can be solved only for about a half of them by homology searches. Prediction methods are thus required, but unfortunately are not fully satisfying. Most prediction methods implicitly assume a unique model for genes. This is an oversimplification as demonstrated by the possibility to group coding sequences into several classes in Escherichia coli and other genomes. As no classification existed for Arabidopsis thaliana, we classified genes according to the statistical features of their coding sequences. A clustering algorithm using a codon usage model was developed and applied to coding sequences from A. thaliana, E. coli, and a mixture of both. By using it, Arabidopsis sequences were clustered into two classes. The CU1 and CU2 classes differed essentially by the choice of pyrimidine bases at the codon silent sites: CU2 genes often use C whereas CU1 genes prefer T. This classification discriminated the Arabidopsis genes according to their expressiveness, highly expressed genes being clustered in CU2 and genes expected to have a lower expression, such as the regulatory genes, in CU1. The algorithm separated the sequences of the Escherichia-Arabidopsis mixed data set into five classes according to the species, except for one class. This mixed class contained 89 % Arabidopsis genes from CU1 and 11 % E. coli genes, mostly horizontally transferred. Interestingly, most genes encoding organelle-targeted proteins, except the photosynthetic and photoassimilatory ones, were clustered in CU1. By tailoring the GeneMark CDS prediction algorithm to the observed coding sequence classes, its quality of prediction was greatly improved. Similar improvement can be expected with other prediction systems.

Algorithms↗

PubMed2001

The sequence determinants of cadherin molecules.

The sequence and structural analysis of cadherins allow us to find sequence determinants-a few positions in sequences whose residues are characteristic and specific for the structures of a given family. Comparison of the five extracellular domains of classic cadherins showed that they share the same sequence determinants despite only a nonsignificant sequence similarity between the N-terminal domain and other extracellular domains. This allowed us to predict secondary structures and propose three-dimensional structures for these domains that have not been structurally analyzed previously. A new method of assigning a sequence to its proper protein family is suggested: analysis of sequence determinants. The main advantage of this method is that it is not necessary to know all or almost all residues in a sequence as required for other traditional classification tools such as BLAST, FASTA, and HMM. Using the key positions only, that is, residues that serve as the sequence determinants, we found that all members of the classic cadherin family were unequivocally selected from among 80,000 examined proteins. In addition, we proposed a model for the secondary structure of the cytoplasmic domain of cadherins based on the principal relations between sequences and secondary structure multialignments. The patterns of the secondary structure of this domain can serve as the distinguishing characteristics of cadherins.

Algorithms↗

PubMed1998

The rational clinical examination. Is this patient having a myocardial infarction?

When faced with a patient with acute chest pain, clinicians must distinguish myocardial infarction (MI) from all other causes of acute chest pain. If MI is suspected, current therapeutic practice includes deciding whether to administer thrombolysis or primary percutaneous transluminal coronary angioplasty and whether to admit patients to a coronary care unit. The former decision is based on electrocardiographic (ECG) changes, including ST-segment elevation or left bundle-branch block, the latter on the likelihood of the patient's having unstable high-risk ischemia or MI without ECG changes. Despite advances in investigative modalities, a focused history and physical examination followed by an ECG remain the key tools for the diagnosis of MI. The most powerful features that increase the probability of MI, and their associated likelihood ratios (LRs), are new ST-segment elevation (LR range, 5.7-53.9); new Q wave (LR range, 5.3-24.8); chest pain radiating to both the left and right arm simultaneously (LR, 7.1); presence of a third heart sound (LR, 3.2); and hypotension (LR, 3.1). The most powerful features that decrease the probability of MI are a normal ECG result (LR range, 0.1-0.3), pleuritic chest pain (LR, 0.2), chest pain reproduced by palpation (LR range, 0.2-0.4), sharp or stabbing chest pain (LR, 0.3), and positional chest pain (LR, 0.3). Computer-derived algorithms that depend on clinical examination and ECG findings might improve the classification of patients according to the probability that an MI is causing their chest pain.

Acute Disease↗

PubMed1994

An algorithmic approach to aspergillus sinusitis.

The effective management of paranasal sinus aspergillosis requires early diagnosis, histological classification, surgery and where appropriate, chemotherapy. Fungal sinusitis may be easily missed unless a high index of suspicion is maintained and specific culture and histology requested. The disease is classified into invasive and noninvasive types, each being divided into two subgroups: invasive aspergillosis may be either fulminant or indolent and noninvasive disease localized or allergic. The literature is reviewed and an algorithmic approach to aspergillus sinusitis proposed. The importance of histologically differentiating invasive from noninvasive aspergillosis prior to selecting the appropriate treatment options is stressed. CT scan should precede definitive surgery, and be used in follow-up. Close and prolonged follow-up is essential.

Algorithms↗

PubMed1994

A case-mix classification system for medical rehabilitation.

Dissatisfaction with Medicare's current system of paying for rehabilitation care has led to proposals for a rehabilitation prospective payment system, but first a classification system for rehabilitation patients must be created. Data for 36,980 patients admitted to and discharged from 125 rehabilitation facilities between January 1, 1990, and April 19, 1991, were provided by the Uniform Data System for Medical Rehabilitation. Classification rules were formed using clinical judgment and a recursive partitioning algorithm. The Functional Independence Measure version of the Function Related Groups (FIM-FRGs) uses four predictor variables: diagnosis leading to disability, admission scores for motor and cognitive functional status subscales as measured by the Functional Independence Measure, and patient age. The system contains 53 FRGs and explains 31.3% of the variance in the natural logarithm length of stay for patients in a validation sample. The FIM-FRG classification system is conceptually simple and stable when tested on a validation sample. The classification system contains a manageable number of groups, and may represent a solution to the problem of classifying medical rehabilitation patients for payment, facility planning, and research on the outcomes, quality, and cost of rehabilitation.

Activities of Daily Living↗

PubMed1998

A new quantitative criterion to distinguish between alpha/beta and alpha+beta proteins (domains).

According to the statistical analysis, it is shown that the differences of the content of alpha-helix and beta-strand between alpha/beta and alpha+beta proteins are of statistical significance. Based on the secondary structure content and the percentage of parallel or anti-parallel strands, any mixed alphabeta protein can be represented by a point in a three-dimensional prism. The distribution of the mapping points for 79 mixed alphabeta proteins (domains), of which 26 are class alpha/beta and 53 are class alpha+beta, shows that the two kinds of points are situated at distinct regions roughly. A new quantitative criterion based on the Fisher discriminant algorithm is proposed to distinguish between the alpha/beta and alpha+beta proteins (domains). Of the 79 proteins 77 are correctly classified (97.5%). As a stringent cross-validation test, the jackknife test shows that of the 79 proteins 77 are correctly classified. The jackknife test accuracy is still 97.5%. These figures indicate the self-consistence and the extrapolating effectiveness of the new quantitative criterion. Applying the new criterion to reclassify the alpha/beta and alpha+beta proteins (domains) in SCOP is also discussed. It is hoped that the new quantitative criterion will be useful for the development of protein classification databases.

Algorithms↗

PubMed1997

Assessment of potential indicators for protein-energy malnutrition in the algorithm for integrated management of childhood illness.

Potential indicators were assessed for the two classifications of protein-energy malnutrition in the guidelines for integrated management of childhood illness: severe malnutrition, which requires immediate referral to hospital, and very low weight, which calls for feeding assessment, nutritional counselling and follow-up. Children aged < 2 years require feeding assessment and counselling as a preventive intervention. For severe malnutrition, we examined 1202 children admitted to a Kenyan hospital for any association of the indicators with mortality within one month. Bipedal oedema indicating kwashiorkor, and two marasmus indicators (visible severe wasting and weight-for-height (WFH) Z-score of < -3) were associated with a significantly increased mortality risk (odds ratios, 3.1-3.9). Very low weight-for-age (WFA) (Z-score of < -4.4) was not associated with an increased risk of mortality. Because first-level health facilities generally lack length-boards, bipedal oedema and visible severe wasting were chosen as indicators of severe malnutrition. To assess potential WFA thresholds for the very low weight classification, our primary source of data came from 1785 Kenyan outpatient children, but we also examined data from surveys in Nepal, Bolivia, and Togo. We examined the performance of WFA at various thresholds to identify children with low WFH and, for children aged < or = 2 years, low height-for-age (HFA). Use of a WFA threshold Z-score of < -2 identified a considerable proportion of children (from 13% in Bolivia to 68% in Nepal) which, in most settings, would pose an enormous burden on the health facility. Among ill children in Kenya, a threshold WFA Z-score of < -3 had a sensitivity of 89-100% to detect children with WFH Z-scores of < -3, and, with an identification rate of 9%, would avoid overburdening the clinics. Potential modifications include use of a more restrictive cut-off in countries with high rates of stunting, or the elimination of the WFA screen in order to concentrate efforts on intervention for all children below the 2-year age cut-off. Key issues in every country include the capacity to provide counselling for many children and linkage to nutritional improvement programmes in the community.

Age Factors↗