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Results for “Intelligent Systems”

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At least 109 records · Page 6Linked to original sources
PubMed1992

Intelligent alarms reduce anesthesiologist's response time to critical faults.

The proliferation of monitors and alarms in the operating room may lead to increased confusion and misdiagnosis unless the information provided is better organized. Intelligent alarm systems are being developed to organize these alarms, on the assumption that they will shorten the time anesthesiologists need to detect and correct faults. This study compared the human response time (the time between the sounding of an alarm and the resolution of a fault) when anesthesiologists used a conventional alarm system and when they used an intelligent alarm system. In a simulated operating room environment, we asked 20 anesthesiologists to resolve seven breathing circuit faults as quickly as possible. Human response time was 62% faster, decreasing from 45 to 17 s, when the intelligent alarm system was used. The standard deviations in response time were only half as large for the intelligent alarm system. It appears that the computer-based neural network in the intelligent alarm system diagnosed faults more rapidly and consistently than did the anesthesiologists. This study indicates that breathing circuit faults may be more rapidly corrected when the anesthesiologist is guided by intelligent alarms.

Anesthesiology↗
PubMed1992

Effects of the fitting parameters of a two-channel compression system on the intelligibility of speech in quiet and in noise.

These experiments were carried out to assess how accurately the gains and compression ratios in a two-channel compression system needed to be set. We used as a research tool a laboratory version of a two-channel full-dynamic-range compression system. The system was initially adjusted to suit each hearing-impaired subject according to the manufacturer's recommendations. Then, further adjustments were made to ensure that speech stimuli were both audible and comfortable over a wide range of sound levels. Finally, the settings of the gains and compression ratios were systematically varied from the adjusted values and the effects of this on the intelligibility of speech in quiet and in noise (12-talker babble, levels of 65 and 75 dB SPL) were measured. The results indicated that speech reception thresholds (SRTs) in quiet were significantly adversely affected by decreases in low-level gain. However, SRTs in noise were relatively unaffected by changes in low-level gain. An exception occurred at the higher noise level used, where increases in the low-level gains (with corresponding increases in compression ratios) had a significant adverse effect on the SRTs. It is concluded that, provided excessive low-level gains (associated with high compression ratios) are avoided, the main criteria for fitting such a system should be listening comfort (i.e. achieving an acceptable tonal balance, and avoiding uncomfortably loud sounds) and an appropriate value of the threshold for detecting speech in quiet (which should be a little below 50 dB SPL).

Acoustic Stimulation↗
PubMed2026

Artificial Intelligence in Predicting Systemic Complications From Retinal Findings: A New Frontier in Precision Medicine.

Innovations in retinal imaging technologies and growing evidence from retinal imaging of systemic and neurodegenerative diseases have begun to explore the utility of retinal imaging in diagnosing these conditions. Since the retina shares embryological origins with the central nervous system and reflects systemic microvascular characteristics, it is well positioned for noninvasive observation of patients' systemic and neural health. Moreover, accessibility of retinal imaging has improved with the increasing number of ophthalmology clinics. Rapid improvements in various deep learning (DL) tools have also catalyzed the automation of retinal imaging analysis. Systems that utilize DL for retinal imaging are being developed to assist with disease recognition, clinical judgment, and prognostic assessment of systemic health. Various imaging modalities are being integrated with existing genomic and clinical data to estimate an individual's predisposition to certain conditions. Contrary to many existing reviews, the objective of this review is to synthesize the most recent clinical and technological evidence on DL-based diagnostic systems for retinal imaging, with a focus on how different network architectures and their combinations have been developed, validated, and applied across systemic disease detection and prediction. Specifically, this review examines the datasets, model validation approaches, and automated diagnostic systems reported in recent literature. It discusses the extent to which these advancements address existing barriers toward real-time diagnostic application across clinical disciplines. Integrating retinal imaging with DL is an innovative and promising approach to precision medicine and health risk reduction.

artificial intelligence↗
PubMed1990

Cancer chronotherapy: a drug delivery challenge.

The toxicity and/or efficacy of more than twenty anticancer agents have been shown in various experimental systems to be dependent upon the circadian timing of their bolus administration or the circadian shaping of their continuous infusion. In cancer patients, the toxicity of several single agents, given either as bolus or infusion, and a growing number of drug combinations have been shown to similarly depend upon their timing. While clinical trials currently underway demonstrate that the circadian stage of drug toxicity and dose intensity each depend upon their circadian timing, definitive investigations of whether or not cancer control and patient survival are similarly dependent upon circadian treatment timing are currently under way. Both clinical trials of treatment timing and chronotherapy depend totally upon the development and use of programmable wearable and implantable, single-channel and multi-channel, open and eventually closed loop delivery systems. First generation intelligent delivery systems are currently available, work well, are economical and are destined, for economic reasons, to be more widely used. When used, each system requires temporal input, making it impossible to avoid specification of drug sequence, interval between drugs or treatment cycles and circadian treatment timing. The advent of biological therapy with cytokines and growth factors makes it likely that the precise timing of cancer therapies will be of growing importance.

Animals↗
PubMedDate not supplied

Automated anesthesia data management and recordkeeping.

It is apparent that judicious application of computer technology to the design and implementation of an automated anesthesia recordkeeping system could afford increased ease of use to the anesthesiologist compared to a manually kept record. Although prototype systems have been developed at academic institutions, and commercially available operating room physiological monitoring systems show increasing capability for some recordkeeping functions, production of an effective AAD-MARKS will depend on the development of suitable display formats and capabilities, markedly improved user interfaces for data input and system control, intelligent graduated alarm systems, and demonstrated reliability, with provision for preservation of critical data and recordkeeping functions and basic physiological data monitoring despite system failure.

Anesthesia↗
PubMed1995

Toward an intelligent wound assessment system.

There is general agreement regarding the need for pressure ulcer assessment methodology which more discretely reflects relevant aspects of wound status than does the commonly used staging system. The Pressure Sore Status Tool (PSST) is one such instrument which was developed with consensual expert input. While the psychometric properties of the PSST have been reported in the literature, the instrument was validated using ET nurses, highly trained wound care specialists, and existed only in manual form. This paper reports results from attempts to establish reliability estimates for healthcare practitioners without extraordinary wound care training or experience. The paper further describes the automation of the PSST and provides examples of pressure ulcer profiles tracked over time. Results indicate that inter-rater reliability with general healthcare practitioners was .78 and intra-rater reliability was .89. The practitioners were able to use the PSST for over six months and the automated system allowed analysis of wound healing profiles that would have been difficult using a manual system. These results imply that movement toward an automated system which makes discriminations regarding the effects of various treatment and intervention strategies is possible and practical.

Aged↗
PubMedDate not supplied

The goal of PACS in Nagoya University Hospital.

In Nagoya University Hospital, a Radiology Intelligent Information System (RIIS) is under construction which will be linked with the Hospital Intelligent Information System (HIIS). RIIS is composed of the radiation oncology information system and the diagnostic radiology information system which is named Imaging Diagnosis Intelligent Information System (IDIIS). IDIIS consists of three parts: (a) the Imaging Diagnosis Management System (IDMS); (b) the Picture Archiving and Communication System (PACS); (c) the Report Generation Support System for Imaging Diagnosis (RGSS-ID). Artificial intelligence methodology is applied to RGSS-ID and IDMS which includes the ordering and scheduling system of diagnostic imaging. IDIIS has an important role to improve the quality of patient care and medical education as well as image management and is an essential component for the implementation of HIIS.

Computer Systems↗
PubMed1991

Computerized measurement of speech intelligibility. I. Development of system and procedures.

An experimental system for the measurement of speech intelligibility has been developed. It uses a Personal Computer (PC), together with appropriate software to handle playback of test words in carrier phrases, presented in a 'closed response' test condition. Information about the intelligibility, based on the correct responses and the confusions, is immediately available due to simultaneous collecting and sorting of subjects' responses. The system works satisfactorily and reliably and has been well received by experimenters as well as by adult test subjects in the age range 18-70 years. From a new Danish standard speech material for audiological purposes, a Multiple Choice speech intelligibility test has been devised. The test is called 4AFC (Four Alternative Forced Choice) and is based on monosyllabic words with consonant confusions. Normative data for the 4AFC test, obtained with the computerized system, are presented in an accompanying paper.

Adolescent↗
PubMed1994

Artificial intelligence in radiology: decision support systems.

Computer-based systems that incorporate artificial intelligence techniques can help physicians make decisions about their patients' care. In radiology, systems have been developed to help physicians choose appropriate radiologic procedures and to formulate accurate diagnoses. These decision support systems use techniques such as rule-based reasoning, artificial neural networks, hypertext, Bayesian networks, and case-based reasoning. This article reviews these artificial intelligence techniques, describes their application in radiology, and discusses the role that decision support systems may play in radiology's future.

Artificial Intelligence↗
PubMed1992

[Intelligent instrumentation in medicine].

The introduction of intelligent robots, expert systems and other forms of intelligent automatization in the current practice of medicine seems to be inevitable. It appears interesting to look back to the efforts that have been done, since the former steps, about three decades ago and consider the prospects in this field for both short and long term. Simultaneously it is interesting to reckon the new aspects which are raised with the evolution of these methodologies such as the responsibility of decisions taken by intelligent systems, the probable advantages, at the present stage, of the interactive systems and the risk of self-learning systems. Some efforts carried out in our department in this field are described.

Artificial Intelligence↗
PubMed1988

Computer-assisted breast cancer grading.

Morphological tumour differentiation has been shown in numerous studies to give a good prognosis in breast cancer, but as histological grading is based upon a subjective assessment of microscopical appearances, difficulties in consistency and reproducibility are inevitable. A review of the many conventional methods served to highlight a common limitation in their approach; lack of structure. We introduce a new approach which seeks to overcome the problem, by formalizing the methods and identifying aspects which are well suited to computer aided analysis, these being incorporated into a microcomputer system facilitating the collection and appraisal of morphometric data. Within the Information Technology Institute (ITRI) at Brighton Polytechnic a research team is carrying out multidisciplinary work into the elucidation of biological systems. This programme, entitled 'Intelligent Medical Systems', used methods of mathematical signal processing and artificial intelligence, applied to a number of areas, one of which is described in this paper. The aim has been to utilize the inherent skill exercised by the histopathologist in interpreting microscopical images, whilst making quantitization more accurate and reproducible. the system has been developed within a highly structured framework and will have applications in teaching and routine histological analysis. The value of artificial intelligence techniques in the wider issues of this area is discussed.

Artificial Intelligence↗