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PubMed2005

Optimal nonmonotonic convergence of the iterative Fourier-transform algorithm.

The increase of the monotonic convergence rate is an important issue for iterative Fourier-transform algorithms. However, the steepest monotonic convergence of the iterative Fourier-transform algorithm does not always promise an optimal solution in the design of a diffractive optical element. The optimal nonmonotonic convergence of the iterative Fourier-transform algorithm is investigated by employing a microgenetic algorithm. The proposed hybrid scheme of the iterative Fourier-transform algorithm and the microgenetic algorithm show nonmonotonic convergence, and this results in a superior design.

Journal Article↗

PubMed1997

Greedy Algorithms for Finding a Small Set of Primers Satisfying Cover and Length Resolution Conditions in PCR Experiments.

Selecting a good collection of primers is very important for polymerase chain reaction (PCR) experiments. Most existing algorithms for primer selection are concerned with computing a primer pair for each DNA sequence. In generalizing the arbitrarily primed PCR, etc., to the case that all DNA sequences of target objects are already known, like about 6000 ORFs of yeast, we may design a small set of primers so that all the targets are PCR amplified and resolved electrophoretically in a series of experiments. This is quite useful because deceasing the number of primers greatly reduces the cost of experiments. Pearson et al. (ISMB 1995: 285-291, 1995; Discrete Appl. Math. 71: 231-246, 1996) consider finding a minimum set of primers covering all given DNA sequences, but their method does not meet necessary biological conditions such as primer amplification and electrophoresis resolution. In this paper, based on the modeling and computational complexity analysis by Doi, we propose algorithms for this primer selection problem. These algorithms do not necessarily minimize the number of primers, but, since basic versions of these problems are shown to be computationally intractable, especially even for approximability with the length resolution condition, this is inevitable. In the algorithms, the amplification condition by a primer pair and the length resolution condition by electrophoresis are incorporated. These algorithms are based on the theoretically well-founded greedy algorithm for the set cover in computer science. Preliminary computational results are presented to show the validity of this approach. The number of computed primers is much less than a half of the number of targets, and hence is less than one forth of the number needed in the multiplex PCR.

Journal Article↗

PubMed1999

A Greedy Algorithm for Minimizing the Number of Primers in Multiple PCR Experiments.

The selection of a suitable set of primers is very important for polymerase chain reaction (PCR) experiments. Most existing algorithms for primer selection are concerned with producing a primer pair for each DNA sequence. However, when all the DNA sequences of the target objects are already known, like the approximately 6,000 yeast ORFs, we may want to design a small set of primers to PCR amplify all the targets, which can then be resolved electrophoretically in a series of experiments. This would be quite useful, because decreasing the number of primers greatly reduces the cost of an experiment. This paper extends the problem of primer selection for a single experiment presented in Doi and Imai (Genome Informatics, 8:43-52, 1997) to primer selection for multiple PCR experiments, and proposes algorithms for the extended problem. The algorithms design primer sets one at a time. We extend the greedy algorithm for one PCR experiment in (Genome Informatics, 8:43-52, 1997) by handling amplified segments in DNA sequences that have been identified by primer pairs already selected and by changing the priorities in the greedy algorithm. This algorithm is applied to real yeast data. The number of primers equaled 85% of the number of identified DNA sequences, which represented more than 90% of all the target DNA sequences. This is 42% the number of primers needed for multiplex PCR. Furthermore, the length of each primer is less than half the length of multiplex PCR primers so the cost of producing the primers is reduced to 20% of the cost in the multiplex PCR case.

Journal Article↗

PubMedDate not supplied

[Assessing an algorithm for the therapeutic swapping of calcium antagonists]

INTRODUCTION AND OBJECTIVE: Therapeutic swapping is one of the activities a Pharmacist ascribed to a Unitary Dose area should undertake. The goal of this work is to assess the impact the definition of a clearly laid-out criteria algorithm for therapeutic swapping regarding calcium antagonists. MATERIAL AND METHODS: The study periods spanned from January to December 2000 before algorithm delivery and from January to April 2001, once the algorithm was in operation. Both the number of prescriptions received at the Pharmacy Department Unitary Dose Area and the number of pharmaceutical acts regarding drugs not included within the Pharmacotherapeutic Guidelines (MNIGFT) and belonging in the Calcium Antagonists Group were collected: direct replacements, active principle swapping, dosage / pharmaceutical formula swapping, and accepted drugs. Study variables were: a) compliance with pharmacotherapeutic guidelines during prescription, such as adjusted number of prescribed MNIGFTs per 1,000 prescriptions, and b) pharmaceutical action adequacy, such as percentage of non-proper therapeutic swaps (performed on the same active principle / dosage, but with better alternatives as defined later in the algorithm). RESULTS: After algorithm implementation a 47.1% decrease in active principles swapping, and a 7.7% decrease in MNIGFT-accepted calcium antagonists, was seen. Similarly, the number of dosage / pharmaceutical formula swaps was increased by 28.6%, and that of non-proper swaps was decreased by 48.0% when compared to the previous period. CONCLUSION: Establishing an algorithm for therapeutic swapping improves compliance with the Pharmacotherapeutic Guidelines during calcium antagonist prescription and the quality of therapeutic swapping as performed by pharmacists regarding this group of drugs.

Journal Article↗

PubMed2003

Development of an evidence-based algorithm for the management of cervical cancer.

OBJECTIVE: To develop a description of the management of cervical cancer to support locally developed, regional guidelines and to identify the level of primary research evidence to support it. DESIGN: Development of a flow-charted algorithm, using regional guidelines and clinician consensus. A Medline literature search for primary research was done to validate the algorithm and selection of papers, to verify if they were valid according to pre-defined criteria and to compare algorithm management with an alternative. MAIN OUTCOME MEASURE: The highest level of evidence for algorithm management was based on the design of the supporting research. RESULTS: Twenty percent of the algorithm is supported by level I evidence (randomised controlled trials), 70% by level II evidence (cohort studies) and 10% by level IV evidence (expert opinion or case series). Level II evidence supports the management of Stage Ia, squamous cell carcinoma by cone biopsy or a simple hysterectomy. This level of evidence also applies to research on the management of Stages Ib-IIa, by radical hysterectomy and pelvic lymphadenectomy followed by radiotherapy, if the lymph nodes are positive. Radiotherapy to treat Stages IIb-IV cervical cancer is supported by level I evidence. The management of Stage I adenocarcinoma is supported by level II evidence. CONCLUSIONS: Evaluations of the effect of informing clinicians of the strengths of the proposed management are now required, as constructing evidence-based algorithms is worthwhile, only if they are likely to affect clinical practice.

Adenocarcinoma↗

PubMed1997

Ploidy determination on histologic sections of breast cancer specimens by image analysis using mathematical correction algorithms.

Several mathematical correction algorithms were developed to solve the problem of the unavoidable measurement of fragmented nuclei when determining DNA ploidy on thin histologic slides. These algorithms were designed for model tissue and until now had not been tested thoroughly on malignant human tissue. We evaluated the use of mathematical correction algorithms applied to measurements on thin histologic sections of breast cancer specimens, with strict control of the section thickness. Fifteen cases of breast carcinoma with known ploidy (5 diploid, 5 tetraploid, and 5 aneuploid breast cancer samples) were included. From each tissue block, we made a single-cell preparation and cut a thin histologic section. We evaluated the thickness of each of these sections according to a recently developed protocol and included only sections with a thickness between 5 and 6 microns. We performed DNA measurements with a custom-made image analyzing system equipped with a 100x oil immersion objective. Histograms of tissue section measurements were corrected according to the algorithms of McCready and Papadimitriou and of Haroske et al. We compared these results with the uncorrected histograms and with the histograms of the single-cell preparations. We also measured the single-cell preparations with a commercially available high-resolution image cytometer. The correlation between both image cytometers used was high (r = 0.99). Histogram correction improved results of tissue section measurements in all of the nondiploid tumors when compared with the uncorrected histograms. There were no significant differences between the correction algorithms used (correlation to the single-cell measurements determined by a linear regression; r = 0.98 for both algorithms). No overcorrection of the histograms occurred. We conclude that reliable DNA tissue section measurements are possible on breast cancer specimens and that such measurements will contribute to our understanding of tumor cell kinetics in small tumor cell populations not detected in single-cell measurements.

Aneuploidy↗

PubMed2026

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans↗

PubMed1999

A comparison of two commercial quantitative electromyographic algorithms with manual analysis.

Quantitative EMG (QEMG) is a useful technique in the evaluation of neuromuscular disease. Manual waveform measurements have been replaced by automated computer-based measurements, but there is no uniformity in computer algorithms used to make waveform measurements. We compared QEMG measurements made by algorithms in two commercially available EMG machines with manual measurements. Motor unit action potentials (MUAPs) were simultaneously fed into the two machines and analyzed using QEMG default settings and automatic waveform marking. The averaged MUAPs were also manually marked. The two algorithms and manual marking did not differ significantly for MUAP amplitude. There were significant differences between algorithms for duration and number of phases. Our study indicates that, although automated algorithms make QEMG more practical, visual inspection, and remarking of each MUAP if needed, is necessary before making clinical judgments from the data.

Action Potentials↗

PubMed1999

Novel real-time R-wave detection algorithm based on the vectorcardiogram for accurate gated magnetic resonance acquisitions.

Electrocardiograph (ECG) triggered or gated magnetic resonance methods are used in many imaging applications. Therefore, a reliable trigger signal derived from to the R-wave of the ECG is essential, especially in cardiac imaging. However, currently available methods often fail mainly due to the artifacts in the ECG generated by the MR scanner itself, such as the magnetohydrodynamic effect and gradient switching noise. The purpose this study was to characterize the accuracy of selected R-wave detection algorithms in an MR environment, and to develop novel approaches to eliminate imprecise triggering. Vectorcardiograms (VCG) in 12 healthy volunteers exposed to 1.5 T magnetic field were digitized and used as a reference data set including manually corrected onsets of R-waves. To define the magnetohydrodynamic effect, the VCGs were characterized in time, frequency, and spatial domains. The selected real-time R-wave detection algorithms, and a new "target-distance" VCG-based algorithm were applied either to standard surface leads calculated from the recorded VCG or to the VCG directly. The flow related artifact was higher in amplitude than the R-wave in 28% of the investigated VCGs which yielded up to 9-16%false positive detected QRS complexes for traditional algorithms. The "target-distance" R-wave detection algorithm yielded a score of 100% for detection with 0.2% false positives and was superior to all the other selected methods. Thus, the VCG of subjects exposed to a strong magnetic field can be use to separate the magnetohydrodynamic artifact and the actual R-wave, and markedly improves the trigger accuracy in gated magnetic resonance scans. Magn Reson Med 42:361-370, 1999.

Adult↗

PubMed2000

A prospective study of an algorithm using cardiac troponin I and myoglobin as adjuncts in the diagnosis of acute myocardial infarction and intermediate coronary syndromes in a veteran's hospital.

BACKGROUND: Accurate and cost-effective evaluation of acute chest pain has been problematic for years. The high prevalence of missed myocardial infarctions (MI) has led to conservative triage behavior on the part of physicians, leading to expensive admissions to coronary care units. New algorithms are sorely needed for more rapid and accurate triage of patients with chest pain to appropriate treatment settings. HYPOTHESIS: We sought to test an algorithm for rapid diagnosis of MI and acute coronary syndromes using cardiac troponin I (cTnI) and myoglobin as adjuncts to creatine kinase (CK)-MB. We hypothesized our algorithm would be both sensitive and specific at early time points, and would allow safe stratification of patients not ruling in by conventional CK-MB criteria. METHODS: This was a 6-month prospective study of 505 consecutive patients who presented with chest pain at a university-affiliated veteran's hospital. The percentage of MIs at various time points was identified using combinations of markers. Safety outcomes were assessed by follow-up of patients discharged home. Cost savings analysis was assessed by surveying the physicians as to whether the use of the algorithm affected their disposition of patients. Forty-nine patients ruled in for MI. Using the combination of cTnI, 2-h doubling of myoglobin, and CK-MB, 37 (76%) ruled in at the time of presentation, 43 (88%) at 2 h, and 100% by 6 h. RESULTS: Cardiac troponin I plus a 2-h myoglobin was as accurate as the combination of all three markers and performed better than CK-MB in detecting patients presenting late and as a predictor for complications when CK-MB was normal. Of the 456 patients with normal markers after 6 h, only 140 were sent to the coronary care unit (CCU), and 176 were sent home. A 3-month follow-up showed minimal adverse events. One-half of physicians completing a survey stated the use of markers changed their disposition of patients, leading to an estimated 6-month cost savings of a half-million dollars. CONCLUSIONS: We developed an algorithm using troponin I and myoglobin as adjuncts to usual CK-MB levels that allowed for rapid and accurate assessment of patients with acute MI. It also afforded physicians important input into their decision making as to how best to triage patients presenting with chest pain. Their comfort in sending home certain subgroups of patients who otherwise would have been admitted to the CCU was rewarded with a good short-term prognosis and a large cost savings to the hospital.

Algorithms↗

PubMed1993

A fast spot segmentation algorithm for two-dimensional gel electrophoresis analysis.

An important issue in the automation of two-dimensional gel electrophoresis image analysis is the detection and quantification of protein spots. A spot segmentation algorithm must detect, define the extent of, and measure the integrated density of spots under a wide variety of actual gel image conditions. Besides these functions, the algorithm must be memory efficient to be able to process very large gel images and do this in a reasonable amount of computation time on low-cost computers, such as workstations and personal computers. We have developed a fast spot segmentation algorithm, extending the GELLAB-II segmenter, which extracts spots in a single raster scanning pass through the gel image. The performance analysis of the algorithm will be given in the paper as well as a discussion of the algorithm.

Algorithms↗

PubMed1999

A comparison of two algorithms, MultiMap and gene mapping system, for automated construction of genetic linkage maps.

Using the GAW11 Problem 2 data set, we compared the performance of two automated map construction algorithms, MultiMap and GMS (Gene Mapping System). The MultiMap algorithm iteratively adds markers in a stepwise manner to the map, while the GMS algorithm seeks to find the best order of the whole set of markers by selective permutations of logically formed subgroups of the markers. While it is difficult to compare these two rather different algorithms, we found that, on these data, GMS performed better than MultiMap, placing more markers in their true order on average, with little order ambiguity. In addition, as the number of markers increased, GMS was less computationally demanding than MultiMap. However, it MultiMap placed a marker, it was almost always in the correct order. In contrast, GMS often placed a group of markers on the wrong end of the map; such incorrect placements occur when the evidence for placement on one end or the other is not strong. Thus, there is room for further algorithmic developments that combine the strengths of both the MultiMap and GMS approaches.

Algorithms↗

PubMed2001

Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data.

Algorithms for performing feature extraction and normalization on high-density oligonucleotide gene expression arrays, have not been fully explored, and the impact these algorithms have on the downstream analysis is not well understood. Advances in such low-level analysis methods are essential to increase the sensitivity and specificity of detecting whether genes are present and/or differentially expressed. We have developed and implemented a number of algorithms for the analysis of expression array data in a software application, the DNA-Chip Analyzer (dChip). In this report, we describe the algorithms for feature extraction and normalization, and present validation data and comparison results with some of the algorithms currently in use.

Algorithms↗

PubMed2006

Quantitative myocardial infarction on delayed enhancement MRI. Part II: Clinical application of an automated feature analysis and combined thresholding infarct sizing algorithm.

PURPOSE: To compare global and regional myocardial infarction (MI) measurements on clinical gadolinium-enhanced magnetic resonance (MR) images using human manual contouring and a computer algorithm previously validated by histopathology, and to study the degree to which visual assessment and human contouring of infarct extent agreed with the computer algorithm. MATERIALS AND METHODS: Infarct size in 20 patients was measured by human manual contouring and with an automated feature analysis and combined thresholding (FACT) computer algorithm. Short-axis slices were divided into myocardial sectors for regional analysis. Extent of infarction was also graded visually by consensus of expert readers and compared to human and computer contouring. RESULTS: Despite good correlations (R = 0.93-0.95) between human contouring and the FACT algorithm, human contouring overestimated infarct size by 3.8% of the left ventricle (23.8% of the MI) area (P < 0.001). Human contouring also overestimated the circumferential extent, transmural extent, and extent of infarction within a sector by 7.1%, 18.2%, and 27.9%, respectively (all P < 0.001). Both consensus reading and human contouring overestimated infarct grades compared with the FACT algorithm (P = 0.002 and P < 0.001). CONCLUSION: Clinically relevant overestimation of MI can occur in visual interpretation and in human manual contouring, particularly with respect to extent of infarction on a regional basis.

Adult↗

PubMed2005

CHASE, a charge-assisted sequencing algorithm for automated homology-based protein identifications with matrix-assisted laser desorption/ionization time-of-flight post-source decay fragmentation data.

We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.

Algorithms↗

PubMed1988

Efficient algorithms for generating interpolated (zoomed) MR images.

This paper discusses the two-dimensional implementation of a number of modified fast Fourier transform (FFT) algorithms that efficiently interpolate (zoom) magnetic resonance (MR) images. If the original image was sampled at a rate satisfying the Nyquist criterion, these algorithms would effectively increase the sampling rate, permitting image details to be more easily discerned. The Skinner interpolating fast Fourier transform (SIFFT) avoids many of the computationally unnecessary complex multiplications that occur when interpolating using the normal fast Fourier transform algorithm. The novel interpolating fast Fourier transform (NIFFT) offers further savings when a subimage is required. Theoretical and experimental timings that compare the use of the normal FFT, SIFFT, and NIFFT algorithms for interpolation are given using magnetic resonance image reconstruction examples. Time savings of a factor of 2 to 4 are possible in typical experimental situations. Time savings of factors of 5 to 20 are possible when zooming images using two-dimensional band selectable digital filtering (2D-BSDF) in combination with decimation and the SIFFT algorithm. In 2D-BSDF, the original MRI data set is reduced in size to retain only those frequency components corresponding to a desired subimage, thereby decreasing the computational load associated with further processing. A significant reduction in computation time is achieved when modeling is combined with 2D-BSDF and SIFFT as fewer points require modeling.

Algorithms↗

PubMed1995

The diminishing variance algorithm for real-time reduction of motion artifacts in MRI.

A technique has been developed whereby motion can be detected in real time during the acquisition of data. This enables the implementation of several algorithms to reduce or eliminate motion effects from an image as it is being acquired. One such algorithm previously described is the acceptance/rejection method. This paper deals with another real-time algorithm called the diminishing variance algorithm (DVA). With this method, a complete set of preliminary data is acquired along with information about the relative motion position of each frame of data. After all the preliminary data are acquired, the position information is used to determine which data frames are most corrupted by motion. Frames of data are then reacquired, starting with the most corrupted one. The position information is continually updated in an iterative process; therefore, each subsequent reacquisition is always done on the worst frame of data. The algorithm has been implemented on several different types of sequences. Preliminary in vivo studies indicate that motion artifacts are dramatically reduced.

Algorithms↗

PubMed1996

Algorithms for extracting motion information from navigator echoes.

Algorithms to reliably detect motion in navigator echoes are crucial to many MRI motion suppression techniques. The accuracy of these algorithms is affected by noise and deformation of navigator echo profile caused by physiologic motion. This study compared the performance of algorithms based on correlation and least squares for extracting displacement information from motion-monitoring navigator echoes, using computer simulation and in vivo imaging. The least squares algorithm was determined to be of higher accuracy than the correlation algorithm against errors caused by noise and profile deformation.

Algorithms↗