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Utterance-based proposed spot diagnostic system of vocal tract malfunction.

It is not surprising that speech recognition by machine, has received a great deal of attention through the techniques of artificial intelligence (AI), like expert systems to support decisions in various intended fields. One proposal that is based on the expert system paradigm is to diagnose a malfunction of the vocal tract during uttering recommended utterances for this purpose. The choice of these utterances is achieved according to the position and the manner of articulation. Four important features of acoustic analysis of speech are, fundamental frequency, F0, Formants, (F1-F5), amplitude, and the harmonic structure (tone vs. noise). The most Candidate features in the proposed diagnostic system are both fundamental frequency and/or the formants. These are considered to be the Core of the intended work. The throat, mouth and nose as the resonating champers will support this attitude and will affect, negatively, the range of the mentioned frequencies when they are out of the anatomical and/or physical functions. The discrete speech (isolated words) as the most recognizable utterances. Will be considered to put aside the difficulties of both connected and continuous word-based recognition. In a diagnostic systems, the generality is an essential issue, that is to consider "Speaker independent" recognizer which needs more efforts during the system training phase. The paper presents a rough (initial) spotting diagnostic system to be the base for a future detailed system for specific defects of precised organs belonging to the vocal tract. Arabic Vowels as well as some Consonants would be the target, taking into account the age range, that is (20-25) years-aged matures. Different recommended utterances, Arabic segmented alphabetic, focused on various points through the vocal apparatus. Speech related waveforms, as well as the associated fundamental frequencies and formants have been considered in the normal and the Corresponding abnormal Cases. The deviations that appeared in the frequency pattern have indicated the defected articulator that is dominant in the intended utterance production. The results illustrated, would be the base for designing a dedicated hardware unit, which may be reliable for the physicians interesting in this field. Human beings communicate with one another primarily by speech, and speech brings human beings closer together speech sounds travel through the air at the rate of about 330 meter per second, whereas impulses travel a long nerve pathways in the body at a rate of about 60 meter per second. The time it takes for a spoken word to be heard and understood by a listener may be shorter than the time it takes as a neural message to travel to the brain, [1]. Speech not only for human Communication, but it also has many applications in different fields. Some of these applications are machine control commands base systems, speech-to-text, and Text-to-speech systems, natural language-based systems, and medical diagnosis systems for vocal tract malfunction, the issue of this paper. One difficulty of speech based-systems is the fact that not everyone speaks the same way, even those who supposedly speak the same language at the same way. The term dialect is used to refer to this variability and is emphasized in case of uttering with different languages. The above discussion is concerning with the social and emotional variability which can be modified with reasonable efforts. The great variabilities, which are difficulty to be manipulated, are belonging to the inheritance and anatomical aspects. So it is worthy and to propose a methodology that can be used globally inspite of different social communities.

Adult↗

A computer assisted orthopaedic surgical system for distal locking of intramedullary nails.

This paper presents a prototype system for computer assisted surgery, the purpose of which is to assist orthopaedic surgeons when performing distal locking of intramedullary nails. This system comprises three components, namely: an Intelligent Image Intensifier, a Trajectory Tactician and an Intelligent Trajectory Guide. The Intelligent Image Intensifier is an X-ray vision system that provides accurate X-ray images. Such images enable the Trajectory Tactician software to analyse the operation site and calculate the trajectory required for a screw to lock an intramedullary nail. This involves the capture of two X-ray images from which are extracted the projections of the nail's edge boundaries and its distal locking holes. Using an analytical mathematical model of the nail, the position and orientation of the nail is determined. The trajectory is then implemented by the surgeon using the Intelligent Trajectory Guide. Evaluation in the laboratory suggests that the system is capable of reliably inserting a locking screw into an intramedullary nail. The rapidity with which this computer assisted method achieves locking should benefit both patient and surgeon by reducing radiation dosage and the length of time required to lock a nail.

Bone Screws↗

Managing complex change in clinical study metadata.

In highly functional metadata-driven software, the interrelationships within the metadata become complex, and maintenance becomes challenging. We describe an approach to metadata management that uses a knowledge-base subschema to store centralized information about metadata dependencies and use cases involving specific types of metadata modification. Our system borrows ideas from production-rule systems in that some of this information is a high-level specification that is interpreted and executed dynamically by a middleware engine. Our approach is implemented in TrialDB, a generic clinical study data management system. We review approaches that have been used for metadata management in other contexts and describe the features, capabilities, and limitations of our system.

Artificial Intelligence↗

Real-time anatomical 3D image extraction for laparoscopic surgery.

Progress in the application of augmented reality to laparoscopic surgery has been limited by the difficulty associated with generating geometric information about the current patient in real time. Structured light techniques are well known methods for generating range images using a camera and projector, but typically fail when faced with biological specimens. We describe techniques and equipment that have shown promise for acquisition of range images for use in a real-time augmented reality system for laparoscopic surgery.

Artificial Intelligence↗

A graph-grammar approach to represent causal, temporal and other contexts in an oncological patient record.

The data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (Therapy Management in Pediatric Oncology), which supports therapy and monitoring in pediatric oncology, a graph-grammar approach has been used to design and implement a graph-oriented patient model which allows the representation of non-trivial (causal, temporal, etc.) clinical contexts. For context acquisition a mouse-based tool has been developed allowing the physician to specify contexts in a comfortable graphical manner. Furthermore, the retrieval of contexts is realized with graphical tools as well.

Adverse Drug Reaction Reporting Systems↗

Beyond antibiotics: artificial intelligence-enabled anti-infective ecosystems for next-generation precision therapeutics against antimicrobial resistance.

The rapid global expansion of antimicrobial resistance (AMR) threatens to undermine decades of progress in infectious disease management and highlights the limitations of conventional antibiotic-centered therapeutic strategies. Although emerging technologies-including antimicrobial peptides, bacteriophage therapy, CRISPR-based antimicrobials, microbiome therapeutics, anti-virulence approaches, nanotechnology-enabled drug delivery, and artificial intelligence (AI)-have individually demonstrated considerable promise, they are predominantly being developed as independent interventions rather than as coordinated components of an integrated therapeutic strategy. This Perspective proposes the Intelligent Anti-Infective Ecosystem (IAIE) as a conceptual systems-level framework that computationally integrates multimodal diagnostics, pathogen genomics, microbiome profiling, AI-assisted decision support, programmable precision therapeutics, ecological monitoring, and longitudinal clinical feedback within a continuously learning dynamically optimized workflow. Unlike existing paradigms that primarily optimize individual technologies or therapeutic decisions, IAIE emphasizes closed-loop coordination among complementary antimicrobial approaches to support precision-guided infection management while preserving microbiome integrity and mitigating resistance selection pressure. We further outline the core components, operational principles, translational challenges, and technology readiness of the major therapeutic platforms that could contribute to such an ecosystem, while distinguishing clinically established interventions from emerging experimental strategies. Importantly, IAIE should be interpreted as a prospective conceptual architecture rather than an existing clinical platform. Its proposed clinical value remains to be established through sequential computational, preclinical, and prospective clinical investigations using standardized microbiological, ecological, and patient-centered outcome measures. By framing antimicrobial innovation within an responsive systems perspective, IAIE provides a roadmap for future multidisciplinary research aimed at integrating artificial intelligence and systems microbiology to enable sustainable management of antimicrobial resistance.

Humans↗

Computer-assisted adult medical diagnosis: subject review and evaluation of a new microcomputer-based system.

Three decades after the conceptual foundation was laid for computer-aided diagnosis, some of its potential has been realized. Systems based on probabilistic reasoning have been developed and applied within limited domains (e.g., acute abdominal pain) and for the general diagnosis of systemic disorders. Less progress has been made in the development and application of diagnostic systems based on "artificial intelligence", reflecting theoretical limits to this application of computers to medicine and the enormity of the task. The presently available probabilistic systems have recently been joined by a new microcomputer-based system, MEDITEL Computer-Assisted Diagnosis, Adult System. The performance of this system was evaluated with both clinical-pathologic conference cases and consecutive admissions with undiagnosed illnesses. The correct diagnosis appeared on the list generated by the system in 80 to 90% of the cases. Experience with this and other systems illustrates current issues in the evaluation of computer systems for aid in diagnosis and of computer-based medical "expert" systems in general. These issues include physician acceptance of these systems and the ethical, legal, and regulatory aspects of computer system application. We conclude that, in appropriately selected cases, the accuracy and efficiency of physician diagnosis can be enhanced with computer assistance, and the risk of overlooking the correct diagnosis can be reduced.

Artificial Intelligence↗

Evaluation stages and design steps for knowledge-based systems in medicine.

After the early experiments in artificial intelligence a methodology is emerging around advanced systems for the management of medical knowledge. The stress is moving away from the implementation of prototypes to the evaluation. It is possible to adapt and to apply this to field evaluation techniques already developed in similar contexts of knowledge management (books, drugs, epidemiology, consultants, etc.). The time is ready for a further step: to envisage a methodology for the design of real systems that cope with the 'knowledge environment' of the user. Every stage of the evaluation process is re-examined here, and considered as a framework to define goals and criteria about a step of design: (1) the impact of the system on the progress of health care provision (priorities, cost-benefit analysis, share of tasks among different media); (2) effectiveness in the end-user's environment and long-term effects on his behaviour (changes in people's role and responsibilities, improvements in the quality of data, acceptance of the system); (3) the intrinsic efficiency of the system apart from the operational context (correctness of the knowledge base, appropriateness of the reasoning). The need to differentiate the test sample into three classes (obvious, typical, atypical) is emphasized, discussing the influence on both evaluation and design. In particular the difficulty of having 'gold standards' on atypical cases, due to the disagreement among the experts, leads to the definition of two alternative attitudes: the 'standardization mode' and the 'brain-storming mode'.

Expert Systems↗

[Expert systems and antibiotic sensitivity test].

Artificial intelligence is a part of computer science that deals with programs mimicking intelligence of man. Artificial intelligence is now used to check the quality of the determination of antibiotics susceptibility of bacteria. This application is useful because antibiotic susceptibility is subject to biological and technical variation that have to be detected. Three types of reasoning are used either by the biologist or by expert systems: low level quality checking dealing with individual results, microbiological interpretation of the whole set of results and medical interpretation of the results. The use of artificial intelligence in these fields is sustained by the structured nature of the knowledge. Two type of expert systems are already of routine use, either based on production rules (ATB plus EXPERT, bioMerieux, La Balme-les-Grottes, France and SIR, 12A, Montpellier, France), or on object-oriented representation of the knowledge (EXPRIM from our laboratory). The main problem is, as usually in artificial intelligence applications, to transfer human expertise into an adapted knowledge base. The advantage of experts systems over man are their reproducibility of answer and their availability.

Artificial Intelligence↗

Multiresolution segmentation of three-dimensional medical images using mathematical morphology techniques.

A semi-automatic method for three-dimensional segmentation of medical images is proposed. A multiresolution representation is achieved through the application of morphological filters, which assures causality for image extrema. This allows for a compact scale space representation, in which each extremum is assigned a scale value. Interactive selection of the interesting extrema of the image is carried out, aided by this scale information and other relevant features. Extrema selected are then used as markers in three-dimensional watersheds calculation. The system has been developed and tested under low cost platforms, and can be the base for totally automatic, knowledge based segmentation systems.

Artificial Intelligence↗

[VIE-PNN: an expert system for calculating parenteral nutrition of intensive care premature and newborn infants].

Daily renewed composition of parenteral nutrition for premature and full-term newborn infants in intensive care is time consuming and prone to inherent calculation errors. We developed a knowledge based system, VIE-PNN (Vienna Expert System for Calculating Parenteral Nutrition of Neonates) for calculating the proposed composition of parenteral nutrition on the basis of the calculating algorithm used at our neonatal intensive care unit. The system needs manual input on postnatal age, body weight, serum electrolytes (or normal values if not available), amount and content of additional oral feeds, venous access (peripheral or central), total amount of fluid intake, and complications such as sepsis (reduced lipid supply) or cholestasis (reduced amino acid supply). The parenteral nutrition proposal may interactively be modified by the attending physician. There are possibilities for error detection to reduce the probability of typing or calculation errors. The system was developed to run on IBM compatible PCs and has been tested clinically. We describe the problem domain, system structure, clinical evaluation of VIE-PNN and the calculation of a standard parenteral nutrition solution from the data stored in the system's database.

Algorithms↗

Crew systems: integrating human and technical subsystems for the exploration of space.

Space exploration missions will require combining human and technical subsystems into overall "crew systems" capable of performing under the rigorous conditions of outer space. This report describes substantive and conceptual relationships among humans, intelligent machines, and communication systems, and explores how these components may be combined to complement and strengthen one another. We identify key research issues in the combination of humans and technology and examine the role of individual differences, group processes, and environmental conditions. We conclude that a crew system is, in effect, a social cyborg, a living system consisting of multiple individuals whose capabilities are extended by advanced technology.

Cybernetics↗

Voice-recognition/knowledgebase reporting systems for ambulatory care patient records.

Speech recognition technology coupled with knowledgebase templates for the evaluation of specific patient complaints together constitute a technology that is currently available for patient reporting in the ambulatory care center. A system based on this technology offers advantages in legibility, speed of record creation, risk management, and reimbursement. It has both direct and indirect educational benefits for the clinician. While training requirements and system costs are reasonable, they continue to be the major stumbling block to widespread use of such systems.

Ambulatory Care Information Systems↗

Design and implementation of a rule based system for ambulatory nursing data management.

In order to effectively organize the use of nursing time during clinic check-in, we designed a forward chaining rule based program for nursing history taking, problem tracking, and documentation. The program consists of a medical logic module trigger engine which identifies relevant rules for nursing history, an interactive question manager for nursing history taking, and a rule generation shell implemented within a specially designed Medical Query Language (MQL) shcema. At clinic check-in, the engine refreshes the rule set for the patient from interaction with the computerized medical record. The interaction driver assists the nurse with tracking of elapsed time, and allows him/her to pursue questions, record data, and create or complete nursing interventions. Nursing question sets and interventions are maintained longitudinally to assure continuity of care. Nursing problems are created on the problem list within the computerized record as the rule system identifies their existence.

Academic Medical Centers↗

VISION2003: virtual learning units for medical training and education.

The project VISION2003 consists of several partners with different professions ranging from medicine to medical informatics, from computer science to didactics. Its aim is the development, testing, introduction and a long-time maintenance of an open, web-based, intelligent and adaptive teaching and learning system for medical education. The system is expected to enhance the acceptance and efficiency of conventional ways of learning by supplementing and supporting them and creating new methods for imparting knowledge ["VISION2003, Lehr-und Lernsysteme in der Medizin: Intelligente und Multimediale, Internetbasierte adaptive und intelligente Autorensysteme für kooperatives Training in der Medizin", (last valid on 17 January 2003) and Ein offenes sprachkonzept für verteilte wissensverarbeitung in der medizin, Tagungsabstract XVI International Congress of the European Federation for Medical Informatics MIE, September 2000]. This is done exemplarily in the specific fields of oncology, accident-surgery and cardiology in consideration of actual standards and didactical measures. The range of possible applications is wide, from electronically accessible scripts through example cases to complex simulations. The main focus of the project is the creation of an open and flexible internet platform for delivering multimedia-based learning units and the development of adaptive and intelligent authoring systems.

Computer-Assisted Instruction↗

Biomedical image processing in pathology: a review.

Pathologists make a diagnostic decision by viewing a specimen and measuring various diagnostically important attributes of an isolated object such as size, shape, darkness, colour and texture. This is a complex process. In recent years, computer-aided image processing and analysis systems have played a significant role in quantitative pathology. This paper summarises basic image processing and analysis techniques and reviews related work in pathology and cytology based on computational image processing since 1987. Firstly, we present a general introduction to image enhancement, segmentation, morphometry and visualisation for those medical colleagues who may not have the necessary background in this area. (The mathematical treatment is kept to minimum and appropriate references are cited to satisfy the more mathematically oriented readers. Selected examples are provided to demonstrate the effects of various basic image processing algorithms on a MRI scan. It should be emphasised that the reviewed techniques are generally used as preprocessing steps in analysing microscopic images and powerful algorithms are more sophisticated and problem-specific.) Secondly, we review image cytometric and histometric methods, standards, calibration and applications. Finally, we touch upon three dimensional confocal image processing and analysis, applications of artificial neural networks, and optical disk database management for recording and retrieving a large number of digitised high resolution images. The development of integrated optical microscope and computer, systems is also briefly described.

Artificial Intelligence↗