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At least 1,351 records · Page 75Linked to original sources
PubMed1994

Preliminary evaluation of an intelligent system for the management of labour.

Over the past 10-15 years, workers using conventional computing approaches have attempted to provide an accurate assessment of fetal condition during labour based on the cardiotocogram (CTG) alone. These have not proved successful perhaps because the correct interpretation of fetal condition also requires physiological knowledge, specific patient information, knowledge of events during labour and considerable practical experience. An intelligent system which considers all the relevant information and embodies expertise may better diagnose fetal condition and support decision making. This study reports the preliminary evaluation of such a system and investigates whether this approach can attain a performance comparable with experienced local clinicians. From a database of 200 high risk labour records, 30 cases were selected; the 9 cases which received clinical intervention for 'fetal-distress' and a further 21 cases selected randomly. The management specified by the system, 3 experienced clinicians (A, B and C) and the actual clinical management were compared in a retrospective blinded review. The experts were found to agree well with each other. Expert A reviewed the cases five months later and was found to be entirely consistent in the management of 28 of the 30 cases. The system's actions were indistinguishable from the experts' and in no case did the system recommend an action not also recommended by at least one experienced reviewer. This study demonstrates the potential of an intelligent system to assist in the management of labour.

Artificial Intelligence↗
PubMed1999

A JAVA implementation of a medical knowledge base for decision support.

Distributed decision support is a challenging issue requiring the implementation of advanced computer science techniques together with tools of development which offer ease of communication and efficiency of searching and control performance. This paper presents a JAVA implementation of a knowledge base model called ARISTOTELES which may be used in order to support the development of the medical knowledge base by clinicians in diverse specialised areas of interest. The advantages that are evident by the application of such a cognitive model are ease of knowledge acquisition, modular construction of the knowledge base and greater acceptance from clinicians.

Artificial Intelligence↗
PubMed2002

Computable decision modules for patient safety in child health care.

OBJECTIVE: To identify controlled evidence from the child health literature on patient conditions and clinical procedures that resulted in unacceptable adverse outcomes. METHODS: Systematic searches of MEDLINE (1966 to 2001), and Cochrane Database of Systematic Reviews (2001) were done. Studies that met the eligibility criteria, were verified for quality of methodology and lack of conflicting studies. A knowledge base of Child Health Safety Modules was then developed. The knowledge base could be used to transfer controlled evidence on potentially harmful interventions into clinical decision support systems conforming with Arden Syntax, a widely applied computer standard. RESULTS: The searches identified knowledge to create 41 Child Health Safety Modules for medications and procedures in child health care, from 29 randomized controlled trials and 12 non-randomized controlled studies. The modules are focused on 28 medication interventions and 13 other clinical procedures. Eighty five percent of the studies were published between 1997-2001. CONCLUSION: An increasing amount of controlled evidence on risks of adverse outcomes in child health is available to alert clinicians when potential planning errors are about to be overlooked.

Artificial Intelligence↗
PubMed2006

Conditional responding is impaired in chronic alcoholics.

Bechara (2003) describes a model for disturbances in executive functions related to addiction. This model involves deficits in decision-making and in suppressing pre-potent representations or response patterns. We tested this model in 29 individuals with long-term heavy alcohol dependency and compared their performance with that of 20 control subjects. Only individuals without memory impairment, with normal intelligence and normal visual response times were included. We examined word fluency, object alternation, spatial stimulus-response incompatibility, extra-dimensional shift learning and decision-making using the Gambling task. We subtracted the performance in a control condition from that of the executive condition, in order to focus specifically on the executive component of each task. Only the object alternation and incompatibility tasks revealed significant differences between the group of alcoholics and the control group. Moreover, response times in the object alternation task correlated with duration of alcohol dependency. The results do not argue in favor of a specific deficit in decision-making or in shifting between relevant representations. We conclude that long-term alcohol abuse leads to an impairment in conditional responding, provided the response depends on former reactions or the inhibition of pre-potent response patterns.

Adult↗
PubMed1994

DILEMMA: logic engineering in primary care, shared care and oncology (AIM Project A2005).

The aim of DILEMMA is to provide tools for the development of decision support systems for use in general medical practice, hospital-based cancer care, and shared care of cancer and cardiology patients. In primary care, the project intends to provide aids to clinical performance in prescribing, referral and the use of clinical guidelines. The demonstrator applications involve telematics and knowledge-based methodology, using an approach termed logic engineering which combines logic programming and software lifecycle methods. DILEMMA will demonstrate systems to assist shared care and home care which should help reduce pressure on secondary health resources and, by disseminating best practice knowledge, improve patient care and patient quality of life.

Artificial Intelligence↗
PubMed1996

An automated intelligent diagnostic system for the interpretation of umbilical artery Doppler velocimetry.

The objective is to develop an automated intelligent diagnostic system for the interpretation of umbilical artery velocity waveforms. An ultrasound instrument with pulsed-wave Doppler is connected to a microcomputer by means of a frame grabber. After data acquisition, umbilical Doppler velocimetry is handled as a pattern recognition (feature extraction and classification) and decision-making problem. Automated image processing (enhancement, smoothing/ thresholding and edge detection) and analysis are used for feature extraction. Six waveform indices obtained by feature extraction are used as input layer to vector quantization which classifies waveforms into six groups. A clinical decision is assigned to each group by the medical expert. Our system is trained by 278 and 380 waveform images of 94 normal and 157 high risk pregnancies, respectively. The system was tested with 193 and 61 images of normal and risky pregnancies; it was demonstrated that sensitivity and specificity of the system are 54.1% and 80.3%, respectively.

Artificial Intelligence↗
PubMed1982

Relationships between McCarthy Scales of children's abilities and teachers' ratings of school achievement.

This study investigated how well the McCarthy Scales of Children's Abilities correlated with teachers' ratings of children's academic achievement. The McCarthy Scales are useful in predicting school achievement of normal children, but more research is needed with learning disabled students. The use of teachers' rating scale with children of low functioning was discussed in light of the recent Larry P. decision.

Achievement↗
PubMed2000

Case-based reasoning computer algorithm that uses mammographic findings for breast biopsy decisions.

OBJECTIVE: We present case-based reasoning computer software developed from mammographic findings to provide support for the clinical decision to perform biopsy of the breast. SUBJECTS AND METHODS: The case-based reasoning system is designed to support the decision to perform biopsy in those patients who have suspicious findings on diagnostic mammography. Currently, between 66% and 90% of biopsies are performed on benign lesions. Our system is designed to help decrease the number of benign biopsies without missing malignancies. Clinicians interpret the mammograms using a standard reporting lexicon. The case-based reasoning system compares these findings with a database of cases with known outcomes (from biopsy) and returns the fraction of similar cases that were malignant. This malignancy fraction is an intuitive response that the clinician can then consider when making the decision regarding biopsy. RESULTS: The system was evaluated using a round-robin sampling scheme and performed with an area under the receiver operating characteristic curve of 0.83, comparable with the performance of a neural network model. If only the cases returning a malignancy fraction of greater than a threshold of 0.10 are sent to biopsy, no malignancies would be missed, and the number of benign biopsies would be decreased by 25%. At a threshold of 0.21, 98%, of the malignancies would be biopsied, and the number of benign biopsies would be decreased by 41%. CONCLUSION: This preliminary investigation indicates that the case-based reasoning approach to computer-aided diagnosis has the potential to improve the accuracy of breast cancer diagnosis on mammography.

Adult↗
PubMedDate not supplied

Analysis of calcium, oxalate, and citrate interaction in idiopathic calcium urolithiasis in children.

The majority of urinary stones in children are composed of calcium oxalate. To investigate the interaction between urinary calcium, oxalate, and citrate as major risk factors for calcium stones formation, their 24-h urinary excretion was determined in 30 children with urolithiasis and 15 normal healthy children. The cutoff points between children with urolithiasis and healthy children, accuracy, sensitivity, and specificity for each risk factor alone as well as for all three taken together were determined. OneR and J4.8 classifiers as parts of the larger data mining software Weka, based on machine learning algorithms, were used for the determination of the cutoff points for differentiation of the children. The decision tree based on J4.8 classifier analysis of all three risk factors together proved to be the best for differentiating stone formers from normal children. In comparison to the accuracy of the differentiation after calcium and oxalate of 80% and 75.6%, respectively, the decision tree showed an accuracy of 97.8%. Even when its stability was tested by the leave-one-out cross-validation procedure, the accuracy remained at a very acceptable percentage of 93.2% correctly classified patients. J4.8 classifier analysis gave a look inside urinary calcium, oxalate, and citrate interaction. Urinary calcium excretion was shown as the most informative in discrimination of the children with urolithiasis from healthy children. However, it was shown that oxalate and citrate excretions might influence the stone formation in a subpopulation of the stone formers. In patients with low urinary calcium, a major role in lithogenesis belongs to oxalate, in some of them alone and in others in conjunction with citrate. Decreased urinary citrate excretion in the presence of increased oxalate excretion may lead to stone formation.

Adolescent↗
PubMed1993

AIDS2: a decision-support tool for decreasing physicians' uncertainty regarding patient eligibility for HIV treatment protocols.

We have developed a decision-support tool, the AIDS Intervention Decision-Support System (AIDS2), to assist in the task of matching patients to therapy-related research protocols. The purposes of AIDS2 are to determine the initial eligibility status of HIV-infected patients for therapy-related research protocols, and to suggest additional data-gathering activities that will decrease uncertainty related to the eligibility status. AIDS2 operates in either a patient-driven or protocol-driven mode. We represent the system knowledge in three combined levels: a classification level, where deterministic knowledge is represented; a belief-network level, where probabilistic knowledge is represented; and a control level, where knowledge about the system's operation is stored. To determine whether the design specifications were met, we presented a series of 10 clinical cases based on actual patients to the system. AIDS2 provided meaningful advice in all cases.

Acquired Immunodeficiency Syndrome↗
PubMed1986

Computer-assisted dental diagnosis.

Computer-assisted dental diagnosis has been discussed from the perspective of applications, decision-making processes, and a specific example of a diagnostic system. Rapid technologic advancement and anticipated developments in the field of artificial intelligence will undoubtedly change both our expectations of future evolutions and our capacity to transform these expectations into reality. The ability of computers to enhance the diagnostic capabilities of practitioners will make automation integral to future dental practice.

Decision Making↗
PubMed1991

An interactive computer simulator of the circulation for knowledge acquisition in cardio-anesthesia.

Knowledge-based decision support systems for use in cardio-anesthesia can provide online support to the anesthesiologist by generating intelligent alarms. However, the acquisition and validation of a consistent knowledge base for this application bears problems related to the transfer of clinical experiences into a rule system. An interactive simulator of the human circulation is presented that supports the process of knowledge acquisition and testing. The simulator can be controlled in realtime by an anesthesiologist during the simulation run thus providing a basis for interdisciplinary discussion of routine as well as critical situations. The output data can be transferred to a knowledge-based system for test purposes. The simulator is currently being used for the development of the Anesthesia Expert Assist System AES-2. With regard to the special application a model of the heart-function was integrated which enables the simulation of heart insufficiency. Simulation runs under various conditions are presented and discussed. The simulator was implemented on an ATARI ST personal computer.

Anesthesiology↗
PubMed1981

[Implications for genetic counselling in regard to sex chromosome aneuploidies diagnosed by amniocentesis (author's transl)].

It is in the detection of chromosomal aneuploidies that amniocentesis currently renders the greatest service. However, when an anomaly of the fetal sex chromosomes is found, the decision of what attitude to hold in counselling the parents poses a real dilemma, due to the importance of phenotypic variation-notably of intelligence and behavior-in individuals with sex chromosome disorders. It is in such situations that the need for information furnished by prospective studies is particularly evident. Prenatal diagnosis of four cases of sex chromosomal polysomy, detected in the course of approximately 600 amniocenteses, is presented, as are the criteria which may guide the parents in their decision to continue or to terminate a pregnancy so affected.

Amniocentesis↗
PubMed2004

Bacterial linguistic communication and social intelligence.

Bacteria have developed intricate communication capabilities (e.g. quorum-sensing, chemotactic signaling and plasmid exchange) to cooperatively self-organize into highly structured colonies with elevated environmental adaptability. We propose that bacteria use their intracellular flexibility, involving signal transduction networks and genomic plasticity, to collectively maintain linguistic communication: self and shared interpretations of chemical cues, exchange of chemical messages (semantic) and dialogues (pragmatic). Meaning-based communication permits colonial identity, intentional behavior (e.g. pheromone-based courtship for mating), purposeful alteration of colony structure (e.g. formation of fruiting bodies), decision-making (e.g. to sporulate) and the recognition and identification of other colonies - features we might begin to associate with a bacterial social intelligence. Such a social intelligence, should it exist, would require going beyond communication to encompass unknown additional intracellular processes to generate inheritable colonial memory and commonly shared genomic context.

Adaptation, Physiological↗
PubMed1999

All Wales surveillance of methicillin-resistant Staphylococcus aureus (MRSA): the first year's results.

Over the last five years, hospitals in Wales have experienced difficulties with increasing numbers of isolates of methicillin-resistant Staphylococcus aureus (MRSA). Continuous total population surveillance of MRSA was introduced with the objectives of gaining an understanding of the extent and variation in time and place of its occurrence, the burden of disease and possible risk factors associated with its isolation and resistance to other antibiotics. All first isolates of MRSA from both hospital and community settings and all isolates of methicillin-sensitive Staphylococcus aureus (MSSA) associated with bacteraemia and cerebrospinal fluid (CSF) isolates detected in medical microbiology laboratories in Wales were collected via CoSurv, a set of interconnected data-base modules for communicable disease control. A data set was collected on each isolate and the patient associated with that isolate and compiled centrally at CDSC (Wales) for all-Wales analysis of the MRSA situation. Surveillance started in January 1996 and at the end of the first year, 2700 new isolates of MRSA had been reported from hospital and community settings, giving a rate of 92.43/100,000 population. The incidence of MRSA from bacteraemias and CSF was 5.20/100,000 compared with 12.70/100,000 for MSSA. MRSA from bacteraemia and CSF was significantly more commonly associated with male patients than MSSA. MRSA patients were significantly older. For all MRSA isolates, the highest reporting rate was in men aged 75+ (647.21/100,000). The highest incidence of invasive disease was also in men aged 75+ (45.69/100,000). Isolates from post-surgical patients were more likely to be involved in invasive disease (OR = 2.59), P < 0.001) than strains from other sources. The majority of isolates were resistant to at least two antibiotics in addition to methicillin, most frequently erythromycin and the fluoroquinolones. Very little resistance to fusidic acid, mupirocin or rifampicin was reported. Continuous total population surveillance has provided a minimum incidence of MRSA in Wales and has allowed a simple and intelligible picture of the problem to be determined, which has been fed back to hospitals to assist decisions on control.

Adolescent↗
PubMed2004

Artificial neural networks for the prediction of response to interferon plus ribavirin treatment in patients with chronic hepatitis C.

Combined therapy using Interferon alfa (IFN) and Ribavirin (RIB) represents the standard treatment in patients with chronic hepatitis C. However, the percentage of responders to this regimen is still low, while its cost and side effects are elevated. Therefore, the possibility to predict patient's response to the above treatment is of paramount importance. The progress in the field of informatics and its large use for decision making has led to the development of novel techniques related to the so-called Artificial Intelligence, even including artificial neural networks (ANNs). In chronic viral hepatitis data are lacking. By means of an artificial neural network (ANN), 300 patients treated with IFN plus RIB were retrospectively analyzed with the aim to predict the response to the treatment. One hundred patients resulted responders and 200 non-responders at the end of treatment and during the follow up. For evaluating the prediction of treatment response, six ANNs with 16 neurons of input, an hidden layer with 7 neurons and an output layer with one neuron were utilized. The ANN model generated a positive predictive value (i.e. posterior probability of treatment response) ranging from 57% to 75% while the negative one (i.e. posterior probability of no response to treatment) was comprised between 52% and 71%. The highest level of diagnostic accuracy was 70%. In conclusion, ANNs appear to be a promising tool in the prediction of treatment response in patients with chronic hepatitis C. However, additional prospective studies are necessary to ultimately validate this predictive method.

Adolescent↗
PubMedDate not supplied

Ceramic materials more durable, suitable for fixed prosthetics.

The practice of dentistry progressed with the recent developments and innovations in dental materials. The clinicians need to be familiar with these materials to successfully incorporate them in their practices. Fixed prosthodontics has assumed a growing role in the practice of restorative dentistry since the application of the lost wax casting technique. With the increased life expectancy, a greater demand of fixed prosthodontics is expected in the future. Recent material and technical and clinical advances have made treatment planing and decision-making more complex; most have attempted to improve current techniques to achieve the ideal pleasant smile. Intelligently planned, well documented, evidence-based research has provided a reliable foundation to many of these advances affecting the practice of fixed prosthodontics. This article will attempt to focus on some of these clinically relevant and applicable developments and briefly review the current literature and encourage pratictioners to review subsequent literature.

Ceramics↗
PubMed1999

[Expert systems in medicine].

Expert systems are software systems developed using different techniques of artificial intelligence that can act parallel to the "human" experts. The main role is consultative These are intelligent information systems that use more then 2000 different rules and that are capable to explain their decisions. Databases of such systems can contain huge number of data about different diseases and therapy modalities. In development of Medical Expert systems the rule of human experts is crucial. The teams of such experts are developing expert system considering the changes in medicine. Several modes of work are available. Consultation mode is used in cases when the diagnosis and treatment is uncertain. The human enter data about symptoms and signs of some medical disorder and computer creates a list of possible diagnosis and additional diagnostic test. Therapy for condition is also suggested. Simulation mode can simulate virtual patient and allows students and doctors to learn mode about some medical conditions. Some expert system as HEPAT can make "Decision Tree" for new-born jaundice. Similar expert system will be available in future for other fields in medicine. Some of expert systems are described in article.

Expert Systems↗