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PubMed2002

Neural network based automated algorithm to identify joint locations on hand/wrist radiographs for arthritis assessment.

Arthritis is a significant and costly healthcare problem that requires objective and quantifiable methods to evaluate its progression. Here we describe software that can automatically determine the locations of seven joints in the proximal hand and wrist that demonstrate arthritic changes. These are the five carpometacarpal (CMC1, CMC2, CMC3, CMC4, CMC5), radiocarpal (RC), and the scaphocapitate (SC) joints. The algorithm was based on an artificial neural network (ANN) that was trained using independent sets of digitized hand radiographs and manually identified joint locations. The algorithm used landmarks determined automatically by software developed in our previous work as starting points. Other than requiring user input of the location of nonanatomical structures and the orientation of the hand on the film, the procedure was fully automated. The software was tested on two datasets: 50 digitized hand radiographs from patients participating in a large clinical study, and 60 from subjects participating in arthritis research studies and who had mild to moderate rheumatoid arthritis (RA). It was evaluated by a comparison to joint locations determined by a trained radiologist using manual tracing. The success rate for determining the CMC, RC, and SC joints was 87%-99%, for normal hands and 81%-99% for RA hands. This is a first step in performing an automated computer-aided assessment of wrist joints for arthritis progression. The software provides landmarks that will be used by subsequent image processing routines to analyze each joint individually for structural changes such as erosions and joint space narrowing.

Algorithms↗

PubMedDate not supplied

Novel lists of 7 +/- 2 known items can be reliably stored in an oscillatory short-term memory network: interaction with long-term memory.

This paper proposes a model for the short-term memory (STM) of unique lists of known items, as, for instance, a phone number. We show that the ability to accurately store such lists in STM depends strongly on interaction with the preexisting long-term memory (LTM) for individual items (e.g., digits). We have examined this interaction in computer simulations of a network based on physiologically realistic membrane conductances, synaptic plasticity processes, and brain oscillations. In the model, seven STMs can be kept active, each in a different gamma-frequency subcycle of a theta-frequency oscillation. Each STM is maintained and timed by an activity-dependent ramping process. LTM is stored by the strength of synapses in recurrent collaterals. The presence of preexisting LTM for an item greatly enhances the ability of the network to store an item in STM. Without LTM, the precise timing required to keep cells firing within a given gamma subcycle cannot be maintained and STM is gradually degraded. With LTM, timing errors can be corrected and the accuracy and order of items is maintained. This attractor property of STM storage is remarkable because it occurs even though there is no LTM that identifies which items are on the list or their order. Multiple known items can be stored in STM, even though their representation is overlapping. However, multiple, identical memories cannot be stored in STM, consistent with the psychophysical demonstration of repetition blindness. Our results indicate that meaningful computation (memory completion) can occur in the millisecond range during an individual gamma cycle.

Computer Simulation↗

PubMed2004

Modulation of two oscillatory networks in the peripheral olfactory system by gamma-aminobutyric acid, glutamate, and acetylcholine in the terrestrial slug Limax marginatus.

The digit-like extensions (the digits) of the tentacular ganglion of the terrestrial slug Limax marginatus are the cell body rich region in the primary olfactory system, and they contain primary olfactory neurons and projection neurons that send their axons to the olfactory center via the tentacular nerves. Two cell clusters (the cell masses) at the bases of the digits form the other cell body rich regions. Although the spontaneous slow oscillations and odor responses in the tentacular nerve have been studied, the origin of the oscillatory activity is unknown. In the present study, we examined the contribution of the neurons in the digits and cell masses to generation of the tentacular nerve oscillations by surgical removal from the whole tentacle preparations. Both structures contributed to the tentacular oscillations, and surgical isolation of the digits from the whole tentacle preparations still showed spontaneous oscillations. To analyze the dynamics of odor-processing circuits in the digits and tentacular ganglia, we studied the effects of gamma-aminobutyric acid, glutamate, and acetylcholine on the circuit dynamics of the oscillatory network(s) in the peripheral olfactory system. Bath or local puff application of gamma-aminobutyric acid to the cell masses decreased the tentacular nerve oscillations, whereas the bath or local puff application of glutamate and acetylcholine to the digits increased the digits' oscillations. Our results suggest the existence of two intrinsic oscillatory circuits that respond differentially to endogenous neurotransmitters in the primary olfactory system of slugs.

Acetylcholine↗

PubMed1998

Incorporation of a set enumeration trees-based classifier into a hybrid computer-assisted diagnosis scheme for mass detection.

RATIONALE AND OBJECTIVES: The authors evaluated whether a hybrid classifier of two independent computer-aided diagnosis (CAD) schemes, the set enumeration (SE) trees approach and an artificial neural network (ANN), could improve the detection of masses on digitized mammograms. The potential benefits resulting from the interpretability of the SE trees model was also explored. MATERIALS AND METHODS: Two hundred thirty verified mass regions and 230 negative but suspicious regions were randomly selected from 618 digitized mammograms. Each region was represented by a 24-parameter feature vector. These features were used as input data for the SE trees and ANN-based schemes. After the positive and negative regions were randomly segmented into five exclusive partitions, a fivefold cross-validation method was applied to evaluate and compare the performance of the SE trees, ANN, and hybrid system in the identification of masses. RESULTS: The performance of the SE trees approach was comparable to that of the ANN. The average area under the receiver operating characteristic (ROC) curves for all five partitions was 0.88 (standard deviation, 0.04). Owing to the relatively low correlation between the region-based results of the SE trees and ANN methods, the hybrid classifier yielded a significantly improved performance, with an area under the ROC curve of 0.94 (standard deviation, 0.02; P < .05). CONCLUSION: The hybrid CAD scheme significantly improved performance. The amenability of the SE trees models to interpretation may aid in the assessment of the importance of specific features.

Artificial Intelligence↗

PubMed1996

The transition to digital media in biocommunications.

As digital audiovisual media become dominant in biomedical communications, the skills of human interface design and the technology of client-server multimedia data networks will underlie and influence virtually every aspect of biocommunications professional practice. The transition to digital communications media will require financial, organizational, and professional changes in current biomedical communications departments, and will require a multi-disciplinary approach that will blur the boundaries of the current biocommunications professions.

Computer Communication Networks↗

PubMed2006

The search for the criteria in reforming health care: evaluation of the spatial accessibility of primary healthcare service.

This article analyzes the spatial accessibility of primary healthcare services, i.e. the population's possibilities to receive healthcare services within an acceptable period of time in healthcare institutions situated in a certain territorial-administrative unit--the municipality. The aim of the study was to develop the technique for the quantitative evaluation of the spatial accessibility of primary healthcare services in different territories. The object of the study was the network of primary healthcare institutions and their subdivisions in the municipalities of Klaipeda, Taurage, and Vilnius districts. The methods of the study were geometrical modeling and applied graphics used for the quantitative determination of the ratios between the total zone area of the accessible primary healthcare institutions and the area of the respective municipal territory. The result of the study was the developed and proposed technique allowing for the evaluation of the spatial accessibility of primary healthcare institutions. The proposed technique of the evaluation of the spatial accessibility of primary healthcare services may be valuable in solving the problems of the development of primary healthcare institutions primarily in the rural regions of Lithuania. The quantitative expression of the evaluation could be used in decision-making related to investments into the development of the primary healthcare institution network in different administrational units of the country. The method of geometrical modeling involving the application of digital graphics may create preconditions for the creation of the geographical information system of the primary healthcare institution network in Lithuania.

Health Care Reform↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗

PubMed2002

An automatic microcalcification detection system based on a hybrid neural network classifier.

A hybrid intelligent system is presented for the identification of microcalcification clusters in digital mammograms. The proposed method is based on a three-step procedure: (a) preprocessing and segmentation, (b) regions of interest (ROI) specification, and (c) feature extraction and classification. The reduction of false positive cases is performed using an intelligent system containing two sub-systems: a rule-based and a neural network sub-system. In the first step of the classification schema 22 features are automatically computed which refer either to individual microcalcifications or to groups of them. Further reduction in the number of features is achieved through principal component analysis (PCA). The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve (A(z)). In particular, the A(z) value for the Nijmegen dataset is 0.91 and for the MIAS is 0.92. The detection specificity of the two sets is 1.80 and 1.15 false positive clusters per image, at the sensitivity level higher than 0.90, respectively.

Automation↗

PubMed2003

[Inter-hospital teledermatology conference using a videophone network].

We organized an inter-hospital teledermatology conference with images through a digital telephone line (ISDN, 128kbps). Our conference system consists of two videophones. A videophone "Phoenix PICSEND-R" (NTT) in the multi-point connection mode is used for discussion among doctors from five hospitals. In addition, using another videophone "Phoenix mini type-S" (NTT), clinical and dermoscopic findings obtained with a digital video camera and a videomicroscope "VMS-1900" (Scalar, Tokyo) respectively were transmitted to Shinshu University Hospital from four rural sites. We have found that the quality of the images obtained is entirely sufficient to make an accurate diagnosis. To calibrate the color and size of skin lesions, a matching sticker "CASMATCH" (Bearmedic, Tokyo) has proved useful. Forty-one times of conference were held from September 1999 to August 2002. In total, the concordance rate between the telediagnosis and the finally confirmed diagnosis was 69% (77 of 112 cases). In cases limited to pigmented skin lesions, the rate was higher (84%) and it was concluded that such conditions are suited for the telediagnosis. The ease with which the data can be manipulated enables us to discuss difficult cases in detail. This style of teleconference system may have benefits for dermatologists especially at rural hospitals in consultation with senior doctors.

Computer Communication Networks↗

PubMed2003

A neural model of how the brain represents and compares multi-digit numbers: spatial and categorical processes.

Both animals and humans represent and compare numerical quantities, but only humans have evolved multi-digit place-value number systems. This article develops a Spatial Number Network, or SpaN, model to explain how these shared numerical capabilities are computed using a spatial representation of number quantities in the Where cortical processing stream, notably the inferior parietal cortex. Multi-digit numerical representations that obey a place-value principle are proposed to arise through learned interactions between categorical language representations in the What cortical processing stream and the Where spatial representation. Learned semantic categories that symbolize separate digits, as well as place markers like 'ty,' 'hundred,' and 'thousand,' are associated through learning with the corresponding spatial locations of the Where representation. Such What-to-Where auditory-to-visual learning generates place-value numbers as an emergent property, and may be compared with other examples of multi-modal cross-modality learning, including synesthesia. The model quantitatively simulates error rates in quantification and numerical comparison tasks, and reaction times for number priming and numerical assessment and comparison tasks. In the Where cortical process, transient responses to inputs are integrated before they activate an ordered spatial map that selectively responds to the number of events in a sequence and exhibits Weber law properties. Numerical comparison arises from activity pattern changes across the spatial map that define a 'directional comparison wave.' Variants of these model mechanisms have elsewhere been used to explain data about other Where stream phenomena, such as motion perception, spatial attention, and target tracking. The model is compared with other models of numerical representation.

Animals↗

PubMed2006

Applications of ENF criterion in forensic audio, video, computer and telecommunication analysis.

This article reports on the electric network frequency criterion as a means of assessing the integrity of digital audio/video evidence and forensic IT and telecommunication analysis. A brief description is given to different ENF types and phenomena that determine ENF variations. In most situations, to reach a non-authenticity opinion, the visual inspection of spectrograms and comparison with an ENF database are enough. A more detailed investigation, in the time domain, requires short time windows measurements and analyses. The stability of the ENF over geographical distances has been established by comparison of synchronized recordings made at different locations on the same network. Real cases are presented, in which the ENF criterion was used to investigate audio and video files created with secret surveillance systems, a digitized audio/video recording and a TV broadcasted reportage. By applying the ENF Criterion in forensic audio/video analysis, one can determine whether and where a digital recording has been edited, establish whether it was made at the time claimed, and identify the time and date of the registering operation.

Journal Article↗

PubMed2003

An artificial neural network for prostate cancer staging when serum prostate specific antigen is 10 ng./ml. or less.

PURPOSE: An artificial neural network was developed to improve the prediction of pathological stage before radical prostatectomy based on variables available at biopsy and clinical parameters. MATERIALS AND METHODS: We used the prospectively accrued European prostate cancer detection data base to train an artificial neural network to predict pathological stage in 200 men with serum prostate specific antigen (PSA) 10 ng./ml. or less who underwent radical prostatectomy. Variables included in the artificial neural network were patient age, serum PSA, free-to-total PSA ratio, PSA velocity, transrectal ultrasound calculated total and transition zone volumes with their associated PSA parameters (transition zone PSA density and PSA density), digital rectal examination and Gleason score on biopsy. Two multilayer perceptron neural networks were trained on the remaining variables. Data on the 200 patients were divided randomly into a training set, a test set and a validation or prospective set. RESULTS: Overall classification accuracy of the artificial neural network was 92.7% and 84.2% for organ confined and advanced prostate cancer staging, respectively. For preoperatively predicting local versus advanced stage the area under the ROC curve for the artificial neural network was significantly larger (0.91) compared with logistic regression analysis (0.83), Gleason score (0.69), PSA density (0.68), prostate transition zone volume (0.63) and serum PSA (0.62) (all p <0.01). CONCLUSIONS: The artificial neural network outperformed logistic regression analysis and correctly predicted pathological stage in more than 90% of the validation patients with serum PSA 10 ng./ml. or less based on clinical, biochemical and biopsy data. In the future artificial neural networks may represent a significant step for improved staging of prostate cancer when counseling patients referred for radical prostatectomy or other curative treatments.

Adult↗

PubMed1997

Normative models and healthcare planning: network-based simulations within a geographic information system environment.

OBJECTIVES: Network analysis to integrate patient, transportation and hospital characteristics for healthcare planning in order to assess the role of geographic information systems (GIS). A normative model of base-level responses of patient flows to hospitals, based on estimated travel times, was developed for this purpose. DATA SOURCES/STUDY SETTING: A GIS database developed to include patient discharge data, locations of hospitals, US TIGER/Line files of the transportation network, enhanced address-range data, and U.S. Census variables. The study area included a 16-county region centered on the city of Charlotte and Mecklenburg County, North Carolina, and contained 25 hospitals serving nearly 2 million people over a geographic area of nearly 9,000 square miles. STUDY DESIGN: Normative models as a tool for healthcare planning were derived through a spatial Network analysis and a distance optimization model that was implemented within a GIS. Scenarios were developed and tested that involved patient discharge data geocoded to the five-digit zip code, hospital locations geocoded to their individual addresses, and a transportation network of varying road types and corresponding estimated travel speeds to examine both patient discharge levels and a doubling of discharge levels associated with total discharges and DRG 391 (Normal Newborns). The Network analysis used location/allocation modeling to optimize for travel time and integrated measures of supply, demand, and impedance. DATA COLLECTION/EXTRACTION METHODS: Patient discharge data from the North Carolina Medical Database Commission, address-ranges from the North Carolina Institute for Transportation Research and Education, and U.S. Census TIGER/Line files were entered-into the ARC/INFO GIS software system for analysis. A relational database structure was used to organize the information and to link spatial features to their attributes. PRINCIPAL FINDINGS: Advances in healthcare planning can be achieved by examining baseline responses of patient flows to distance optimization simulations and healthcare scenarios conducted within a spatial context that uses a normative model to integrate characteristics of population, patients, hospitals, and transportation networks. Model runs for the defined scenarios indicated that a doubling of the 1991 patient discharge levels resulted in an areal constriction of the service areas to those zip codes immediately adjacent to the hospitals, thereby leaving substantial areas unassigned to hospitals during the allocation process, but that doubling the demand for obstetrics care (DRG 391) resulted in little change in the pattern of accessibility to care as indicated by the size, orientation, and pattern of the service areas. CONCLUSIONS: The GIS-Network system supported "what if" simulations, portrayed service areas within a spatial context, integrated disparate data in the execution of the location/allocation model, and used estimated travel time along a transportation network instead of Euclidean distance for calculating accessibility. The results of the simulations suggest that the GIS-Network system is an effective approach for exploring a variety of healthcare scenarios where changes in the supply, demand, and impedance variables can be examined within a spatial context and where variations in system trajectories can be simulated and observed.

Computer Communication Networks↗

PubMed1997

Neural net-based identification of cells expressing the p300 tumor-related antigen using fluorescence image analysis.

We report on preliminary investigations of the use of an image analysis system to perform preliminary algorithmic classification of images of fluorochrome-labeled cells followed by capture of gray-level images of potentially abnormal cells for analysis by a neural network. Cells were labeled with an antibody against a bladder cancer tumor-associated antigen, and the neural net was used to distinguish true-positive cells from negative cells, false-positive cells (autofluorescent or nonspecific labeling), and cell-sized artifacts. Gray-level cell images were digitized and processed for analysis by a feed-forward neural network using back-propagation. The network was trained and tested with two independent image sets. Various network configurations and activation functions were investigated, including a sinusoidal activation function. At high power, the network agreed completely with the human observer's classification. At low power, a strong clustering of cells classified by the network with expert classification was seen, while the neural network showed roughly 75% concordance with the human observer. In addition, a set of four features extracted from raw cell images were investigated. The features were: shape factor, texture, area, and average pixel intensity. A network trained with these features performed better than one operating with gray-level images. We conclude that using neural networks to recognize and classify images captured by an image analysis microscope is feasible.

Antigens, Neoplasm↗

PubMed1980

A new hypothesis for synaptic modification: an interactive process between postsynaptic competition and presynaptic regulation.

Based on recent physiological observations, a new hypothesis for the algorithm for synaptic modification is proposed: an interactive process between postsynaptic competition and presynaptic regulation controls the synaptic modification, and both functions obey the same competitive rule. A fundamental algorithm for the competitive rule is proposed and analysed. The interactive process is deomposed into two procedures. The first one is a postsynaptic competition, in which all synapses making contact with the same postsynaptic cell compete for their terminal sites, and the postsynaptic cell makes demands for synaptic modification upon the presynaptic cells. The second one is a presynaptic regulation, in which the presynaptic cell regulates the postsynaptic demands and determines the net amount of the modification for each snyapse originating from it. The performance of the alforithm has been simulated on a digital computer. The initial structure of the simulated neural network consists of randomly-connected presynaptic and postsynaptic cells, with no other structures assumed. After repetitive presentations of a uniform stimulus, the basic configurations of neural connections (one-to-one, one-to-many, many-to-one and many-to-many connections) are organized in dependence on the parameters of the algorithm.

Axonal Transport↗

PubMedDate not supplied

The anthroform biorobotic arm: a system for the study of spinal circuits.

This paper reports the design, construction, and testing of a replica of the human arm, which aims to be dynamically as well as kinematically accurate. The arm model is actuated with McKibben pneumatic artificial muscles, and controlled by a special purpose digital signal processing system designed to simulate spinal neural networks in real time. An artificial muscle spindle has also been designed and tested. Design and test data are reviewed, and the paper describes how we hope to use the system to improve our understanding of the reflexive control of human movement and posture.

Arm↗

PubMed2005

Benefits of the DICOM modality performed procedure step.

A few years ago, the Digital Imaging and Communications in Medicine standard introduced a network transaction that is initiated by modality equipment, mainly at the beginning and at the end of the acquisition. This transaction, the Modality Performed Procedure Step (MPPS), is sent to the Picture Archiving and Communication System and/or to the Radiology Information System. It carries information about what really has been performed by the modality equipment during acquisition. In this paper, we present MPPS and discuss its benefits. We show how MPPS enables efficient radiology workflow and how it ensures accuracy and completeness of imaging information. We think our paper helps bridge the gap between MPPS implementation and deployment. By understanding all the MPPS benefits, the end user becomes aware of the great enhancement in patient care that this transaction provides.

Computer Communication Networks↗

PubMedDate not supplied

Image management and communication--a legal perspective.

This paper outlines the legal issues that arise in the context of digital diagnostic image management and communication. At the heart of the study is the digital image which is manipulated, processed, communicated, stored compressed and archived, and which is difficult to ascertain from a legal point of view because of its intangible nature. At issue is, on the one hand, data protection and security and, on the other hand, legal problems as to the images' evidential force, procedural and legal admissibility and most important uncertainties about the liabilities of those involved in handling the digital image.

Computer Communication Networks↗