Utilización de metodologías de Inteligencia Artificial y sus aplicaciones en El Salvador

El presente artículo intenta dar una pequeña perspectiva de cómo el uso de las metodologías basadas en Inteligencia Artificial (IA) podrían contribuir en la solución de problemas reales del país: como la eficiencia y eficacia en consultas médicas del Instituto del Seguro Social Salvadoreño (ISSS), toma de decisiones políticas importantes, resolución de juicios legales, evasión de impuestos, aprobación de créditos, optimización de recursos, etc. El documento describe brevemente diferentes técnicas de Inteligencia Artificial (IA) tales como Sistemas Expertos (SE), Razonamiento Basados en Casos (RBC), Redes Neuronales Artificiales (RNA) y Algoritmos Genéticos (AG) entre otras, y menciona en forma sintetizada algunas áreas críticas en las que podrían aplicarse en el país con éxito. El objetivo principal de este artículo es dar a conocer otras alternativas hasta ahora desconocidas por las instituciones del Estado para la resolución de problemas nacionales importantes

Aerospace Medicine and Biology: A cumulative index to the 1982 issues

This publication is a cumulative index to the abstracts contained in the Supplements 229 through 240 of Aerospace Medicine and Biology: A continuing Bibliography. It includes three indexes: subject, personal author, and corporate source

Image and Signal Processing in Intravascular Ultrasound

Intravascular ultrasound (rvUS) is a new imaging mOdality providing real-time, crosssectional, high-resolution images of the arterial lumen and vessel wall. In contrast to conventional x-ray angiography that only displays silhouette views of the vessel lumen, IVUS imaging permits visualization of lesion morphology and accurate measurements of arterial cross-sectional dimensions in patients. These unique capabilities have led to many important clinical applications including quantitative assessment of the severity, restenosis, progression of atherosclerosis, selection and guidance of catheterbased therapeutic procedures and short- and long-term evaluation of the outcome of an intravascular intervention. Like the progress of other medial imaging modalities, the advent of IVUS techniques has brought in new challenges in the field of signal and image processing. Quantitative analysis of IVUS images requires the identification of arterial structures such as the lumen and plaque within an image. Manual contour tracing is well known to be time consuming and subjective. Development of an automated contour detection method may improve the reproducibility of quantitative IVUS and avoid a tedious manual procedure. Computerized three-dimensional (3D) reconstruction of an IVUS image series may extend the tomographic data to a more powerful volumetric assessment of the vessel segment. Obviously, this could not be achieved without the advance of 3D image processing techniques. Furthermore, it is demonstrated that processing of the original radio frequency (RF) echo signals provides an efficient means to improve the IVUS image quality as well as a new approach to extract volumetric flow information. The goals of the studies reported in this thesis are therefore directed toward development of video image and RF signal processing techniques for image enhancement, automated contour detection, 3D reconstruction and flow imaging. In this chapter several IVUS scanning mechanisms and some background information about ultrasonic imaging are briefly introduced. The principles of different video-based contour detection approaches and examples of contour detection in echocardiograms are discussed. Subsequently, applications of RF analysis in IVUS images are reviewed, followed by the scope of this thesis in the final part

Coronary Angiography

In the intervening 10 years tremendous advances in the field of cardiac computed tomography have occurred. We now can legitimately claim that computed tomography angiography (CTA) of the coronary arteries is available. In the evaluation of patients with suspected coronary artery disease (CAD), many guidelines today consider CTA an alternative to stress testing. The use of CTA in primary prevention patients is more controversial in considering diagnostic test interpretation in populations with a low prevalence to disease. However the nuclear technique most frequently used by cardiologists is myocardial perfusion imaging (MPI). The combination of a nuclear camera with CTA allows for the attainment of coronary anatomic, cardiac function and MPI from one piece of equipment. PET/SPECT cameras can now assess perfusion, function, and metabolism. Assessing cardiac viability is now fairly routine with these enhancements to cardiac imaging. This issue is full of important information that every cardiologist needs to now

Future Supply of Medical Radioisotopes for the UK Report 2014

The UK has no research nuclear reactors and relies on the importation of 99Mo and other medical radioisotopes (e.g. Iodine-131) from overseas (excluding PET radioisotopes). The UK is therefore vulnerable not only to global shortages, but to problems with shipping and importation of the products. In this context Professor Erika Denton UK national Clinical Director for Diagnostics requested that the British Nuclear Medicine Society lead a working group with stakeholders including representatives from the Science & Technology Facilities Council (STFC) to prepare a report. The group had a first meeting on 10 April 2013 followed by a working group meeting with presentations on 9th September 2013 where the scope of the work required to produce a report was agreed. The objectives of the report are: to describe the status of the use of medical radioisotopes in the UK; to anticipate the potential impact of shortages for the UK; to assess potential alternative avenues of medical radioisotope production for the UK market; and to explore ways of mitigating the impact of medical radioisotopes on patient care pathways. The report incorporates details of a visit to the Cyclotron Facilities at Edmonton, Alberta and at TRIUMF, Vancouver BC in Canada by members of the report team.Comment: 121 page

A novel case-based reasoning approach to radiotherapy dose planning

In this thesis, novel Case-Based Reasoning (CBR) methods were developed to be included in CBRDP (Case-Based Reasoning Dose Planner) -an adaptive decision support system for radiotherapy dose planning. CBR is an artificial intelligence methodology which solves new problems by retrieving solutions to previously solved similar problems stored in a case base. The focus of this research is on dose planning for prostate cancer patients. The records of patients successfully treated in the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK, were stored in a case base and were exploited using case-based reasoning for future decision making. After each successful run of the system, a group based Simulated Annealing (SA) algorithm automatically searches for an optimal/near optimal combination of feature weights to be used in the future retrieval process of CBR. A number of research issues associated with the prostate cancer dose planning problem and the use of CBR are addressed including: (a) trade-off between the benefit of delivering a higher dose of radiation to cancer cells and the risk to damage surrounding organs, (b) deciding when and how much to violate the limitations of dose limits imposed to surrounding organs, (c) fusion of knowledge and experience gained over time in treating patients similar to the new one, (d) incorporation of the 5 years Progression Free Probability and success rate in the decision making process and (e) hybridisation of CBR with a novel group based simulated annealing algorithm to update knowledge/experience gained in treating patients over time. The efficiency of the proposed system was validated using real data sets collected from the Nottingham University Hospitals. Experiments based on a leave-one-out strategy demonstrated that for most of the patients, the dose plans generated by our approach are coherent with the dose plans prescribed by an experienced oncologist or even better. This system may play a vital role to assist the oncologist in making a better decision in less time; it incorporates the success rate of previously treated similar patients in the dose planning for a new patient and it can also be used in teaching and training processes. In addition, the developed method is generic in nature and can be used to solve similar non-linear real world complex problems

A novel case-based reasoning approach to radiotherapy dose planning

In this thesis, novel Case-Based Reasoning (CBR) methods were developed to be included in CBRDP (Case-Based Reasoning Dose Planner) -an adaptive decision support system for radiotherapy dose planning. CBR is an artificial intelligence methodology which solves new problems by retrieving solutions to previously solved similar problems stored in a case base. The focus of this research is on dose planning for prostate cancer patients. The records of patients successfully treated in the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK, were stored in a case base and were exploited using case-based reasoning for future decision making. After each successful run of the system, a group based Simulated Annealing (SA) algorithm automatically searches for an optimal/near optimal combination of feature weights to be used in the future retrieval process of CBR. A number of research issues associated with the prostate cancer dose planning problem and the use of CBR are addressed including: (a) trade-off between the benefit of delivering a higher dose of radiation to cancer cells and the risk to damage surrounding organs, (b) deciding when and how much to violate the limitations of dose limits imposed to surrounding organs, (c) fusion of knowledge and experience gained over time in treating patients similar to the new one, (d) incorporation of the 5 years Progression Free Probability and success rate in the decision making process and (e) hybridisation of CBR with a novel group based simulated annealing algorithm to update knowledge/experience gained in treating patients over time. The efficiency of the proposed system was validated using real data sets collected from the Nottingham University Hospitals. Experiments based on a leave-one-out strategy demonstrated that for most of the patients, the dose plans generated by our approach are coherent with the dose plans prescribed by an experienced oncologist or even better. This system may play a vital role to assist the oncologist in making a better decision in less time; it incorporates the success rate of previously treated similar patients in the dose planning for a new patient and it can also be used in teaching and training processes. In addition, the developed method is generic in nature and can be used to solve similar non-linear real world complex problems