Resumen-Los costos continuos, altos e innecesarios de la tecnología, la escasa atención del paciente, las decisiones tomadas por personas con poca experiencia y el desperdicio de recursos públicos dedicados a la salud, generan la necesidad de desarrollar un proceso racional y sistemático para la incorporación de equipos médicos. El objetivo de este trabajo fue hacer que un método comience con una recopilación de información a través de una revisión de la literatura y la implementación de una encuesta para diagnosticar el estado de los procesos de incorporación en diferentes instituciones de salud y saber cuáles son las etapas críticas y los pasos a seguir en cada uno de ellos. El método se implementó en un caso real con la adquisición de dos tecnologías: el acelerador lineal y un esterilizador de vapor. El método fue validado con dos expertos responsables de la adquisición de estos equipos para determinar su usabilidad e importancia en el proceso de incorporación de la tecnología biomédica. La validación mostró resultados cuantitativos y positivos para ambas tecnologías, ya que los expertos estuvieron satisfechos con cada uno de los aspectos evaluados y el informe final proporcionado por el método.Palabras Clave-Tecnología biomédica; incorporación; tecnología; adquisición. Method of Strategic incorporation of BioMedical technology for health inStitutionSAbstract-The continued high and unnecessary costs of technology, poor patient care, decisions made by people with little experience and waste of public resources devoted to health. All generate a need to develop a rational and systematic process for the incorporation of medical equipment. The aim of this work was to create such a method through collection of information, a literature review and implementation of a survey to diagnose the status of the processes of incorporation into different healthcare institutions and learn the critical stages and steps to be performed in each. The method was implemented in a real case with the acquisition of two technologies, a linear accelerator and a steam sterilizer. The method was validated with two experts responsible for the acquisition of this equipment to determine its usability and importance in the process of incorporation of biomedical technology. Validation showed quantitative and positive results for both technologies because the experts were satisfied with each of the aspects evaluated and the final report provided by the method.
General anesthesia is currently defined in the context of its use in clinical care [1]. The mechanism by which anesthetic drugs induce general anesthesia is not well understood. There is therefore a need to incorporate neurophysiological characterizations into the definition and understanding of anesthesia. Distinct patterns in the electroencephalogram have been associated with anesthesia-induced loss of consciousness [2][3][4] and are used as part of protocols to monitor integrity of brain function [5]. However, the transition to unconsciousness during a gradual induction of general anesthesia has not been studied systematically.Here we report results of multivariate frequency-domain characterizations of propofol induced changes in the scalp EEG of human subjects performing a behavioral task. In this task subjects were asked to respond to auditory stimuli while loss of consciousness was induced through gradual increase in propofol dosage. Subsequently, the dose was decreased and the subjects recovered consciousness. EEG was recorded from 64 channels sampled at 5000 Hz. Behavioral data was gathered throughout the recording period and subjects were required to keep their eyes closed.We characterize the temporal dynamics of the EEG through an eigenvalue decomposition of the time and frequency dependent cross spectral matrix. We find that the state of anesthesia induced unconsciousness as assessed from behavioral data is strongly correlated with the persistence of a single dominant mode in the high alpha low beta range (see Figure 1) concentrated in the frontal channels. As the propofol dose was decreased the contribution of this mode decreased as well. Our findings suggest that general anesthesia induced unconsciousness may be accompanied by a single dominant mode at selected frequencies between the frontal channels.
The rapid pace of change in technology, business models, and work practices is causing ever-increasing strain on the global workforce. Companies in every industry need to train professionals with updated skill-sets in a rapid and continuous manner. However, traditional educational models — university classes and in-person degrees— are increasingly incompatible with the needs of professionals, the market, and society as a whole. New models of education require more flexible, granular and affordable alternatives. MIT is currently developing a new educational framework called Agile Continuous Education (ACE). ACE describes workforce level education offered in a flexible, cost-effective and time-efficient manner by combining individual, group, and real-life mentored learning through multiple traditional and emerging learning modalities. This paper introduces the ACE framework along with its different learning approaches and modalities (e.g. asynchronous and synchronous online courses, virtual synchronous bootcamps, and real-life mentored apprenticeships and internships) and presents the MIT Refugee Action Hub (ReACT) as an illustrative example. MIT ReACT is an institute-wide effort to develop global education programs for underserved communities, including refugees, displaced persons, migrants and economically disadvantaged populations, with the goal of promoting the learner’s social integration and formal inclusion into the job market. MIT ReACT’s core programs are the Certificate in Computer and Data Science (CDS) and the MicroMasters in Data, Economics and Development Policy, which consist of a combination of online courses, bootcamps, and global apprenticeships. Currently, MIT ReACT has regional presence in the Middle East and North Africa, East Africa, South America, Asia, Europe and North America.
In 2021 the United States Air Force (USAF) and the Department of Defence (DoD) entered into a collaboration with multiple units within the Massachusetts Institute of Technology (MIT) to develop a new academic program focusing on Artificial Intelligence (AI) training. Given the size and the diversity within the body of USAF employees, the goal of this collaboration is to design and implement an innovative program that will achieve maximum learning outcomes at scale for learners with diverse roles and educational backgrounds. This program is now piloting and evaluating three different learning journeys addressing three different groups of USAF employees (USAF leaders and decision makers; technology developers; and daily frontend technology users). The learning journeys were designed based on each group’s specific professional needs and academic backgrounds, and they include combinations of online synchronous and asynchronous courses and face-to-face activities. The program’s pilot is currently underway and evaluation research findings are informing the next program iterations. The ultimate goal of this program is to formulate general recommendations on how to serve large numbers of diverse learners at scale in an optimum way. In addition to an evaluation pilot study, MIT experts on AI and the Science of Learning have been asked to review the program and their feedback will be integrated into the next program iteration. This paper presents the three learning journeys as originally designed to serve the three first diverse cohorts of learners, as well as the plan for future improvement and implementation of the program.
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