Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice

Purpose: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression. / Methods: Nonsystematic literature review using the search combinations "Artificial Intelligence," "Deep Learning," "Machine Learning," "Neural Networks," "Bayesian Networks," "Glaucoma Diagnosis," and "Glaucoma Progression." Information on sensitivity and specificity regarding glaucoma diagnosis and progression analysis as well as methodological details were extracted. / Results: Numerous AI strategies provide promising levels of specificity and sensitivity for structural (e.g. optical coherence tomography [OCT] imaging, fundus photography) and functional (visual field [VF] testing) test modalities used for the detection of glaucoma. Area under receiver operating curve (AROC) values of > 0.90 were achieved with every modality. Combining structural and functional inputs has been shown to even more improve the diagnostic ability. Regarding glaucoma progression, AI strategies can detect progression earlier than conventional methods or potentially from one single VF test. / Conclusions: AI algorithms applied to fundus photographs for screening purposes may provide good results using a simple and widely accessible test. However, for patients who are likely to have glaucoma more sophisticated methods should be used including data from OCT and perimetry. Outputs may serve as an adjunct to assist clinical decision making, whereas also enhancing the efficiency, productivity, and quality of the delivery of glaucoma care. Patients with diagnosed glaucoma may benefit from future algorithms to evaluate their risk of progression. Challenges are yet to be overcome, including the external validity of AI strategies, a move from a "black box" toward "explainable AI," and likely regulatory hurdles. However, it is clear that AI can enhance the role of specialist clinicians and will inevitably shape the future of the delivery of glaucoma care to the next generation. / Translational Relevance: The promising levels of diagnostic accuracy reported by AI strategies across the modalities used in clinical practice for glaucoma detection can pave the way for the development of reliable models appropriate for their translation into clinical practice. Future incorporation of AI into healthcare models may help address the current limitations of access and timely management of patients with glaucoma across the world

A review of techniques for spatial modeling in geographical, conservation and landscape genetics

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space

Molecular identification of Coccidioides spp. in soil samples from Brazil

<p>Abstract</p> <p>Background</p> <p>Since 1991 several outbreaks of acute coccidioidomycosis (CM) were diagnosed in the semi-arid Northeast of Brazil, mainly related to disturbance of armadillo burrows caused by hunters while digging them for the capture of these animals. This activity causes dust contaminated with arthroconidia of <it>Coccidioides posadasii</it>, which, once inhaled, cause the mycosis. We report on the identification of <it>C. posadasii </it>in soil samples related to outbreaks of CM.</p> <p>Results</p> <p>Twenty four soil samples had their DNA extracted and subsequently submitted to a semi-nested PCR technique using specific primers. While only 6 (25%) soil samples were positive for <it>C. posadasii </it>by mice inoculation, all (100%) were positive by the molecular tool.</p> <p>Conclusion</p> <p>This methodology represents a simple, sensitive and specific molecular technique to determine the environmental distribution of <it>Coccidioides </it>spp. in endemic areas, but cannot distinguish the species. Moreover, it may be useful to identify culture isolates. Key-words: 1. Coccidioidomycosis. 2. <it>Coccidioides </it>spp. 3. <it>C. posadasii</it>. 4. Semi-arid. 5. Semi-nested PCR</p

General framework for estimating the ultimate precision limit in noisy quantum-enhanced metrology

The estimation of parameters characterizing dynamical processes is central to science and technology. The estimation error changes with the number N of resources employed in the experiment (which could quantify, for instance, the number of probes or the probing energy). Typically, it scales as 1/N^(1/2). Quantum strategies may improve the precision, for noiseless processes, by an extra factor 1/N^(1/2). For noisy processes, it is not known in general if and when this improvement can be achieved. Here we propose a general framework for obtaining attainable and useful lower bounds for the ultimate limit of precision in noisy systems. We apply this bound to lossy optical interferometry and atomic spectroscopy in the presence of dephasing, showing that it captures the main features of the transition from the 1/N to the 1/N^(1/2) behaviour as N increases, independently of the initial state of the probes, and even with use of adaptive feedback.Comment: Published in Nature Physics. This is the revised submitted version. The supplementary material can be found at http://www.nature.com/nphys/journal/v7/n5/extref/nphys1958-s1.pd

Postural assessment of patients with non-conventional knee endoprosthesis

Objective:To investigate the correlation between the sagittal and frontal alignment and possible postural asymmetries found in patients submitted to total knee stent placement for osteosarcoma.Methods:Twenty two individuals were divided into two groups according to tumor location: femur group (13 patients) and tibia group (nine patients), who were evaluated through postural analysis software (SAPO).Results:No statistically significant difference was found between groups, supporting previous result showing that both groups present the same postural asymmetries.Conclusion:We conclude that both groups have the same postural imbalances, especially the knee of the affected limb that presents hyperextension and center of gravity shifted anteriorly and laterally to the non-affected limb, indicating changes in weight bearing and influencing the gait pattern and balance. Level of Evidence II, Prospective Comparative Study.Universidade Federal de São Paulo (UNIFESP) Instituto de Oncologia PediátricaUNIFESP, Instituto de Oncologia PediátricaSciEL

Nonlinear vortex light beams supported and stabilized by dissipation

We describe nonlinear Bessel vortex beams as localized and stationary solutions with embedded vorticity to the nonlinear Schr\"odinger equation with a dissipative term that accounts for the multi-photon absorption processes taking place at high enough powers in common optical media. In these beams, power and orbital angular momentum are permanently transferred to matter in the inner, nonlinear rings, at the same time that they are refueled by spiral inward currents of energy and angular momentum coming from the outer linear rings, acting as an intrinsic reservoir. Unlike vortex solitons and dissipative vortex solitons, the existence of these vortex beams does not critically depend on the precise form of the dispersive nonlinearities, as Kerr self-focusing or self-defocusing, and do not require a balancing gain. They have been shown to play a prominent role in "tubular" filamentation experiments with powerful, vortex-carrying Bessel beams, where they act as attractors in the beam propagation dynamics. Nonlinear Bessel vortex beams provide indeed a new solution to the problem of the stable propagation of ring-shaped vortex light beams in homogeneous self-focusing Kerr media. A stability analysis demonstrates that there exist nonlinear Bessel vortex beams with single or multiple vorticity that are stable against azimuthal breakup and collapse, and that the mechanism that renders these vortexes stable is dissipation. The stability properties of nonlinear Bessel vortex beams explain the experimental observations in the tubular filamentation experiments.Comment: Chapter of boo