Augmented reality: Seeing the benefits is believing

There is always something taken away when there are added functionalities. Does the concept of wearing augmented reality that digitally provides situational awareness create an upside that outweighs what it takes away for rifleman skills? The supercharged hearing, six senses for those equipped, broader view of sight, picking up smells, changes in lights and shadows, slightest change in the near environment: With all these close-action skills, will augmented reality create more distraction than enhancement? Is it too early to push digital situational awareness all the way down to the soldier in maneuver units? Is the upside present

Teaching Modeling to Engineers in an Undergraduate Simulation Course

A significant challenge in teaching simulation to undergraduate students is to find a way to allow them to model a real world referent system within time and student skill constraints. Several research sources highlight not only the important challenge of model development (Garcia and Ceneno, 2009, Tako, 2011) but also the increased need for model development instruction among engineers (Grasas et. al., 2013, Saltzman and Roeder, 2013). One approach to this challenge is to use a general purpose discrete event simulation software package within the course, but this presents two challenges. Teaching the package to the students takes significant time, and the package introduces limitations which may restrict their ability to model certain real-world referents, particularly in the engineering domain. A conceptual approach to solving this problem is to use a model development paradigm that abstracts away the interface to the simulation infrastructure while still allowing the students to use the full expressive nature of a programming language. Two undergraduate courses at the United States Military Academy employed this strategy via the Discrete Events Specification System – Distributed Modeling Framework (DEVS-DMF) (Kewley et. al, 2016). The DEVS abstraction allowed students to think about their model as a simple state change function with defined inputs and outputs, and DMF allowed them to program in a cloud-based Jupyter Notebook using the Python language. Students in a combat modeling course employed a variety of models to understand drone jamming, and students in an engineering capstone project employed models to account for human factors in rifle marksmanship. The effectiveness of this approach was assessed through student grades, exit-interviews, and course-end surveys. These assessments showed an increased understanding of the model development process, and students also reported greater ownership of their models. However, this experiment also highlighted some weaknesses in their understanding of underlying methodologies and programming skills

Panoramic Augmented Reality for Persistence of Information in Counterinsurgency Environments (PARPICE)

Modern Counter-Insurgency (COIN) and Irregular Warfare (IW) are increasingly complex. Contributing to this complexity is the need to develop and maintain a mental map of relevant environmental and historical factors and their interactions, generated from disparate sources of information that must be organized, processed and integrated. Compounding this challenge is the fact that mental pictures cannot easily be passed from one soldier to the next. This is a problem when the tactical situation dictates frequent changes in unit Areas of Operations (AOs), and particularly in cases where units rotate on a regular basis. When units hand over an AO, the incoming unit must quickly rebuild a mental picture and narrative of its operating environment. Because of this, historical organizational knowledge is lost that could otherwise increase combat effectiveness and reduce casualties. This thesis discusses a prototype architecture for a system that will enable a vehicle crew commander to spatially input, organize and view fused tactical information through placement of 3D interactive symbols directly into the real-life on-site scene from the vehicle perspective. A panoramic camera, dashboard monitor and head tracker give the commander a complete view of the vehicle surroundings for improved situational awareness, and a 360-degree LiDAR scanner supplies depth information for accurate annotation geo-location. This system is intended to generate greater situational understanding of the complex environment present in COIN operations, in order to allow greater performance and survivability of the vehicle crew. Such a system, if fielded, can create the ability to add numerous other capabilities to the combat vehicle crew.http://archive.org/details/panoramicaugment109455057JIEDDO; HQDA G-8 CAAUS Army (USA) authorApproved for public release; distribution is unlimited

Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps

Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under- and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments.Patient summaryThis mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.</p

The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations

Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info

Combining Free Text and Structured Electronic Medical Record Entries to Detect Acute Respiratory Infections

The electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).A manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis.An adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.Structured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties

Comparing Notes: Recording and Criticism

This chapter charts the ways in which recording has changed the nature of music criticism. It both provides an overview of the history of recording and music criticism, from the advent of Edison’s Phonograph to the present day, and examines the issues arising from this new technology and the consequent transformation of critical thought and practice

Postoperative outcomes in oesophagectomy with trainee involvement

BACKGROUND: The complexity of oesophageal surgery and the significant risk of morbidity necessitates that oesophagectomy is predominantly performed by a consultant surgeon, or a senior trainee under their supervision. The aim of this study was to determine the impact of trainee involvement in oesophagectomy on postoperative outcomes in an international multicentre setting. METHODS: Data from the multicentre Oesophago-Gastric Anastomosis Study Group (OGAA) cohort study were analysed, which comprised prospectively collected data from patients undergoing oesophagectomy for oesophageal cancer between April 2018 and December 2018. Procedures were grouped by the level of trainee involvement, and univariable and multivariable analyses were performed to compare patient outcomes across groups. RESULTS: Of 2232 oesophagectomies from 137 centres in 41 countries, trainees were involved in 29.1 per cent of them (n = 650), performing only the abdominal phase in 230, only the chest and/or neck phases in 130, and all phases in 315 procedures. For procedures with a chest anastomosis, those with trainee involvement had similar 90-day mortality, complication and reoperation rates to consultant-performed oesophagectomies (P = 0.451, P = 0.318, and P = 0.382, respectively), while anastomotic leak rates were significantly lower in the trainee groups (P = 0.030). Procedures with a neck anastomosis had equivalent complication, anastomotic leak, and reoperation rates (P = 0.150, P = 0.430, and P = 0.632, respectively) in trainee-involved versus consultant-performed oesophagectomies, with significantly lower 90-day mortality in the trainee groups (P = 0.005). CONCLUSION: Trainee involvement was not found to be associated with significantly inferior postoperative outcomes for selected patients undergoing oesophagectomy. The results support continued supervised trainee involvement in oesophageal cancer surgery

Models of classroom assessment for course-based research experiences

Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education